• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.187-195
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• 2008

In MANET, it is important to efficiently manage data objects and traffic to improve network throughput and response time. This paper proposes a connection-degree based data object search and replication scheme in mobile ad-hoc networks. In this method, information about the path data object providers is stored at the cache of a cluster header at which lots of queries arrive, so that, to reduce the load of the cluster header, replicas can be created at its neighboring nodes. The method proposes an algorithm that picks up a cluster header among mobile nodes and makes it possible to search for and utilize adaptive and up-to-date information in MANET. The method is expected to be effective since it enables access to data objects in spite of broken links among mobile nodes with an enhancement in network response time of searching and a decrease in communication costs. The efficiency of this system was verified via simulation.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.501-510
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• 2006

The self-organizing super peer ring P2P search scheme improves search performance of the existing unstructured peer-to-peer systems, in which super peers with high capacity constitute a ring structure and all peer in the system utilize the ring for publishing or querying their keys. In this paper, we further improves the performance of the self-organizing ring by adaptively changing its super peer ratio according to the status of the entire system. By using PSO, the optimized super peer ratio can be maintained within the system. Through simulations, we show that our self-organizing super peer ring optimized by PSO outperforms not only the fixed super peer ring but also the self-organizing super ring with fixed ratio in the aspect of query success rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1222-1228
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• 2006

In this paper, I propose a video watermaking method using adaptive threshold value and half-cell motion vector. Conventional method cause a lot of change of motion vectors and bring about a falling-off in invisibility, because it search embedding condition about whole macroblocks and watermarks are embedded in arbitrary motion vectors. Proposed method improve invisibility and decrease in number of change of motion vectors, because it create threshold value by using power of motion vector(PMV), and watermarks are embedded in motion vectors which greater than threshold value. Consequently, proposed method improve invisibility with on an average 5.4 dB ~9.3dB according to video bit-stream.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.276-292
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• 2004

In this paper. we present methods that extract lung regions from chest EBT(electron beam tomography) images then segment the extracted lung region into lung lobes. We use histogram based thresholding and mathematical morphology for extracting lung regions. For detecting pulmonary fissures, we use edge detector and knowledge-based search method. We suggest this edge detector, which uses adaptive filter scale, to work very well for real edge and insensitive for edge by noise. Our experiments showed about 95% accuracy or higher in extracting lung regions and about 5 pixel distance error in detecting pulmonary fissures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4603-4624
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• 2016

In this paper, a new reversible watermarking algorithm with adaptive embedding threshold matrix is proposed. Firstly, to avoid the overflow and underflow, two flexible thresholds, TL and TR, are applied to preprocess the image histogram with least histogram shift cost. Secondly, for achieving an optimal or near optimal tradeoff between the embedding capacity and imperceptibility, the embedding threshold matrix, composed of the embedding thresholds of all blocks, is determined adaptively by the combination between the composite chaos and the average energy of Integer Wavelet Transform (IWT) block. As a non-liner system with good randomness, the composite chaos is suitable to search the optimal embedding thresholds. Meanwhile, the average energy of IWT block is calculated to adjust the block embedding capacity, and more data are embedded into those IWT blocks with larger average energy. The experimental results demonstrate that compared with the state-of-the-art reversible watermarking schemes, the proposed scheme has better performance for the tradeoff between the embedding capacity and imperceptibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.404-421
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• 2020

A reversible data hiding scheme in JPEG compressed bitstreams is proposed, which could avoid decoding failure and file expansion by means of removing of bitstreams corresponding to high frequency coefficients and embedding of secret data in file header as comment part. We decode original JPEG images to quantified 8×8 DCT blocks, and search for a high frequency as an optimal termination point, beyond which the coefficients are set to zero. These blocks are separated into two parts so that termination point in the latter part is slightly smaller to make the whole blocks available in substitution. Then spare space is reserved to insert secret data after comment marker so that data extraction is independent of recovery in receiver. Marked images can be displayed normally such that it is difficult to distinguish deviation by human eyes. Termination point is adaptive for variation in secret size. A secret size below 500 bits produces a negligible distortion and a PSNR of approximately 50 dB, while PSNR is also mostly larger than 30 dB for a secret size up to 25000 bits. The experimental results show that the proposed technique exhibits significant advantages in computational complexity and preservation of file size for small hiding capacity, compared to previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5489-5511
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• 2019

The performance of evolutionary algorithms can be seriously weakened when constraints limit the feasible region of the search space. In this paper we present a constrained multi-objective optimization algorithm based on adaptive ε-truncation (ε-T-CMOA) to further improve distribution and convergence of the obtained solutions. First of all, as a novel constraint handling technique, ε-truncation technique keeps an effective balance between feasible solutions and infeasible solutions by permitting some excellent infeasible solutions with good objective value and low constraint violation to take part in the evolution, so diversity is improved, and convergence is also coordinated. Next, an exponential variation is introduced after differential mutation and crossover to boost the local exploitation ability. At last, the improved crowding density method only selects some Pareto solutions and near solutions to join in calculation, thus it can evaluate the distribution more accurately. The comparative results with other state-of-the-art algorithms show that ε-T-CMOA is more diverse than the other algorithms and it gains better in terms of convergence in some extent.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.