• Journal of Industrial Technology
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• v.15
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• pp.41-50
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• 1995

This paper presents a technique for estimating distribution of data stored in a database. This technique is very useful for accurate selectivity estimation, which is essential in query optimization and physical database design. To maintain data distribution, we employ the directory of the multilevel grid file, a multidimensional dynamic file organization. The major advantage of our technique is that data distribution information is maintained dynamically in the multilevel grid file. In contrast, other static methods such as the histogram method use static date structures, which requires periodic restructuring. Furthermore, we propose a method for keeping the abstract information of data distribution in main memory. This is advantageous in the situation where the size of main memory is not sufficient. Finally, We also suggest formulas for calculating selectivies of various queries based on our data distribution information.

• Journal of Service Research and Studies
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• v.6 no.1
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• pp.71-81
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• 2016

An efficient reversible data hiding algorithm was proposed in this paper. The original image can be recovered from the stego-image without distortion during the embedded data are extracted from the stego-image. The embedding data are greater than that of the previous algorithm and the PSNR value of the stego-image is guaranteed to be greater than 48dB. The performance of the proposed algorithm was proved by experimental results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.652-657
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• 2015

BitTorrent is an innovative protocol related to file-sharing and file-transferring, which allows users to receive pieces of files from multiple sharer on the Internet to make the pieces into complete files. In reality, however, free distribution of illegal or copyright related video data is counted for crime. Difficulty of regulation on the copyright of data on BitTorrent is caused by the fact that data is transferred with the pieces of files instead of the complete file formats. Therefore, the classification process of file formats of the digital contents should take precedence in order to restore digital contents from the pieces of files received from BitTorrent, and to check the violation of copyright. This study has suggested SVM classifier for the classification of digital files, which has the feature vector of histogram differential on the pieces of files. The suggested classifier has evaluated the performance with the division factor by applying the classifier to three different formats of video files.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.114-121
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• 2008

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system for Environment Education Contents which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted form query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.5
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• pp.432-441
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• 2007

Image processing methods for an extraction of a nuclear fuel rod image and visualization methods of the RGB color data were studied with a sectional image of spent fuel assembly. The fuel rod images could be extracted by using a histogram analysis, an edge detection and RGB rotor data. In these results, a size of the spent fuel assembly could be measured by using a histogram analysis method and a shape of the spent fuel rod could be observed by using an edge detection method. Finally, a various analyses were established for status of the spent fuel assembly by realized various 3D images for the color data in an image of a spent fuel assembly.

• Atmosphere
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• v.22 no.4
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• pp.415-427
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• 2012

$CO_2$ is the most important trace gas related to climate change. Therefore, understanding surface carbon sources and sinks is important when seeking to estimate the impact of $CO_2$ on the environment and climate. CarbonTracker, developed by NOAA, is an inverse modeling system that estimates surface carbon fluxes using an ensemble Kalman filter with atmospheric $CO_2$ measurements as a constraint. In this study, to investigate the capability of CarbonTracker as an analysis tool for estimating surface carbon fluxes in Asia, an experiment with a nesting domain centered in Asia is performed. In general, the results show that setting a nesting domain centered in Asia region enables detailed estimations of surface carbon fluxes in Asia. From a rank histogram, the prior ensemble spread verified at observational sites located in Asia is well represented with a relatively flat rank histogram. The posterior flux in the Eurasian Boreal and Eurasian Temperate regions is well analyzed with proper seasonal cycles and amplitudes. On the other hand, in tropical regions of Asia, the posterior flux does not differ greatly from the prior flux due to fewer $CO_2$ observations. The root mean square error of the model $CO_2$ calculated by the posterior flux is less than the model $CO_2$ calculated by the prior flux, implying that CarbonTracker based on the ensemble Kalman filter works appropriately for the Asia region.

• Journal of radiological science and technology
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• v.43 no.2
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• pp.105-114
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• 2020

This study aimed to assess of beam-matching accuracy for an 8 MV beam between the same model linear accelerators(Linac) commissioned over two years. Two models were got the customer acceptance procedure(CAP) criteria. For commissioning data for beam-matched linacs, the percentage depth doses(PDDs), beam profiles, output factors, multi-leaf collimator(MLC) leaf transmission factors, and the dosimetric leaf gap(DLG) were compared. In addition, the accuracy of beam matching was verified at phantom and patient levels. At phantom level, the point doses specified in TG-53 and TG-119 were compared to evaluate the accuracy of beam modelling. At patient level, the dose volume histogram(DVH) parameters and the delivery accuracy are evaluated on volumetric modulated arc therapy(VMAT) plan for 40 patients that included 20 lung and 20 brain cases. Ionization depth curve and dose profiles obtained in CAP showed a good level for beam matching between both Linacs. The variations in commissioning beam data, such as PDDs, beam profiles, output factors, TF, and DLG were all less than 1%. For the treatment plans of brain tumor and lung cancer, the average and maximum differences in evaluated DVH parameters for the planning target volume(PTV) and the organs at risk(OARs) were within 0.30% and 1.30%. Furthermore, all gamma passing rates for both beam-matched Linacs were higher than 98% for the 2%/2 mm criteria and 99% for the 2%/3 mm criteria. The overall variations in the beam data, as well as tests at phantom and patient levels remains all within the tolerance (1% difference) of clinical acceptability between beam-matched Linacs. Thus, we found an excellent dosimetric agreement to 8 MV beam characteristics for the same model Linacs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.856-873
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• 2011

Reversible watermarking is an open problem in information hiding field, with embedding the encoded bit '1' or '0' into some sensitive images, such as the law enforcement, medical records and military images. The technique can retrieve the original image without distortion, after the embedded message has been extracted. Histogram-based scheme is a remarkable breakthrough in reversible watermarking schemes, in terms of high embedding capacity and low distortion. This scheme is lack of capacity control due to the requirement for embedding large-scale data, because the largest hidden capacity is decided by the amount of pixels with the peak point. In this paper, we propose a reversible watermarking scheme to enlarge the number of pixels with the peak point as large as possible. This algorithm is based on an adaptive edge-guided interpolation, furthermore, hides messages by interpolation-error, i.e. the difference between the original and interpolated image value. Simulation results compared with other state-of-the-art reversible watermarking schemes in this paper demonstrate the validity of the proposed algorithm.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.293-300
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• 2018

We propose a moving object extraction and tracking method for improvement of animal identification and tracking technology. First, we propose a method of merging separated moving objects into a moving object by using FCM (Fuzzy C-Means) clustering algorithm to solve the problem of moving object loss caused by moving object extraction process. In addition, we propose a method of extracting data from a moving object and a method of counting moving objects to determine the number of clusters in order to satisfy the conditions for performing FCM clustering algorithm. Then, we propose a method to continuously track merged moving objects. In the proposed method, color histograms are extracted from feature information of each moving object, and the histograms are continuously accumulated so as not to react sensitively to noise or changes, and the average is obtained and stored. Thereafter, when a plurality of moving objects are overlapped and separated, the stored color histogram is compared with each other to correctly recognize each moving object. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.