• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1246-1257
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• 2004

To find an optimal solution with genetic algorithm, it is desirable to maintain the population sire as large as possible. In some cases, however, the cost to evaluate each individual is relatively high and it is difficult to maintain large population. To solve this problem we propose a novel genetic algorithm based on fuzzy clustering, which considerably reduces evaluation number without any significant loss of its performance by evaluating only one representative for each cluster. The fitness values of other individuals are estimated from the representative fitness values indirectly. We have used fuzzy c-means algorithm and distributed the fitness using membership matrix, since it is hard to distribute precise fitness values by hard clustering method to individuals which belong to multiple groups. Nine benchmark functions have been investigated and the results are compared to six hard clustering algorithms with Euclidean distance and Pearson correlation coefficients as fitness distribution method.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1431-1437
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• 2011

This paper proposes a novel watermarking algorithm that protects digital copyrights and is robust to attacks. Watermarks are embedded in the subband including the significant part of the signal such as a pitch. Generally, the subband containing the pitch has the biggest energy. In order to find this subband, wavelet packet transform is used to decompose the subbands and their energy are calculated. The signal of the selected subbands is transformed in frequency domain using FFT. The watermarks are embedded using QIM for samples higher than a certain threshold. The blind detection uses the Euclidean distance. The proposed method shows less than 5% BER in the audio watermark benchmarking.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.303-307
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• 2011

This paper describes an audio watermarking using Quantization Index Modulation (QIM) on significant peaks in frequency domain. The audio signal is broken up into L samples length frames with non-overlapping and rectangular window. The zero-crossing rate of each frame is calculated for decision whether it is proper to be watermarked or not. If the frame is legitimate, frequency magnitude response is computed by discrete Fourier transform. For the QIM, we set the quantization step size based on maximum value of frequency magnitude response and select n significant peaks with w samples around them in frequency domain, totally $n{\times}(w+1)$ samples. Finally, watermark embedding is performed. Decoder extract watermarks based on Euclidean distance, that is a blind detection. The proposed method is robust against many attacks of watermark benchmark.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.463-468
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• 2001

We propose a new similarity measure based on relative membership function (RMF). In this paper, the RMF is suggested to represent the relativity between fuzzy subsets easily. Since the shape of the RMF is determined according to the values of its parameters, we can easily represent the relativity between fuzzy subsets by adjusting only the values of its parameters. Hence, we can easily reflect the relativity among individuals or cultural differences when we represent the subjectivity by using the fuzzy subsets. In this case, these parameters may be regarded as feature points for determining the structure of fuzzy subset. In the sequel, the degree of similarity between fuzzy subsets can be quickly computed by using the parameters of the RMF. We use Euclidean distance to compute the degree of similarity between fuzzy subsets represented by the RMF. In the meantime, we present a new linguistic approximation method as an application area of the proposed similarity measure and show its numerical example.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.9
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• pp.668-676
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• 2018

In satellite communications, a modulation technique with a low peak-to-average power ratio, high transmission efficiency, and low bit error rate(BER) is required, and differential amplitude and phase shift keying(DAPSK) modulation technique has been appraised as a technology that meets these requirements. However, because conventional DAPSK modulation uses a regular constellation diagram, the Euclidean distance between the symbols in the inner concentric circles of the constellation are quite short. Such a characteristic degrades the BER. In this paper, we propose a DAPSK system that uses an efficient constellation assignment to improve the performance of existing DAPSK systems and evaluate the performance of the proposed scheme. From the simulation results, we confirm that the proposed 16-DAPSK system achieves an signal-to-noise ratio gain of 0.8 dB over the conventional approach at a BER condition of $10^{-4}$ when the number of symbols used in the symbol detector of the receiver is 2.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.317-324
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• 2012

Recently, coordination task of similarity between national R&D programs is emphasized on view from the R&D investment efficiency. But the previous similarity search method like text-based similarity search which using keyword of R&D projects has reached the limit due to deviation of document's quality. For the solve the limitations of text-based similarity search using the keyword extraction, in this study, utilization of R&D project's technical classification will be discussed as a new similarity search method when analyzed of similarity between national R&D programs. To this end, extracts the Science and Technology Standard Classification of R & D projects which are collected when national R&D Survey & analysis, and creates peculiar vector model of each R&D programs. Verify a reliability of this study by calculate the cosine-based and Euclidean distance-based similarity and compare with calculated the text-based similarity.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1307-1314
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• 2015

This study proposed a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. The algorithm proposed detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). Also, by applying the feature vector obtained for SVM, face areas can be tested. After the testing, the feature vector is applied to LDA and using Euclidean distance in the 2nd dimension, the final analysis and matching is performed. The algorithm proposed in this study could increase the stability and accuracy of recognition rates and as a large amount of calculation was not necessary due to the use of two dimensions, real-time recognition was possible.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.672-679
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• 2011

In this paper, detection algorithm of face region based on skin color of in the TV images is proposed. In the first, reference image is set to the sampled skin color, and then the extracted of face region is candidated using the Euclidean distance between the pixels of TV image. The eye image is detected by using the mean value and standard deviation of the component forming color difference between Y and C through the conversion of RGB color into CMY color model. Detecting the lips image is calculated by utilizing Q component through the conversion of RGB color model into YIQ color space. The detection of the face region is extracted using basis of knowledge by doing logical calculation of the eye image and lips image. To testify the proposed method, some experiments are performed using front color image down loaded from TV color image. Experimental results showed that face region can be detected in both case of the irrespective location & size of the human face.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.425-430
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• 2015

This paper is a study to improve the classification efficiency of rotating objects by using deep neural networks to which a deep learning algorithm was applied. For the classification experiment of rotating objects, COIL-20 is used as data and total 3 types of classifiers are compared and analyzed. 3 types of classifiers used in the study include PCA classifier to derive a feature value while reducing the dimension of data by using Principal Component Analysis and classify by using euclidean distance, MLP classifier of the way of reducing the error energy by using error back-propagation algorithm and finally, deep learning applied DBN classifier of the way of increasing the probability of observing learning data through pre-training and reducing the error energy through fine-tuning. In order to identify the structure-specific error rate of the deep neural networks, the experiment is carried out while changing the number of hidden layers and number of hidden neurons. The classifier using DBN showed the lowest error rate. Its structure of deep neural networks with 2 hidden layers showed a high recognition rate by moving parameters to a location helpful for recognition.

• Journal of the Korean Geotechnical Society
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• v.27 no.11
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• pp.83-92
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• 2011

The random and heterogeneous pore structure is a significant factor that dominates physical and mechanical behaviors of soils such as fluid flow and geomechanical responses driven by loading. The characterization method using non-destructive testing such as micro X-ray CT technique which has a high resolution with micrometer unit allows to observe internal structure of soils. However, the application has been limited to qualitatively observe 2D and 3D CT images and to obtain the void ratio at macro-scale although the CT images contain enormous information of materials of interests. In this study, we constructed the 3D particle and pore structures based on sequentially taken 2D images of glass beads and quantitatively defined complex pore structure with void cell and void channel. This approach was enabled by implementing image processing techniques that include coordinate transformation, binarization, Delaunay Triangulation, and Euclidean Distance Transform. It was confirmed that the suggested algorithm allows to quantitatively evaluate the distribution of void cells and their connectivity of heterogeneous pore structures for glass beads.