• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.165-178
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• 2000

Bayesian methods are considered for the multiple caputure-recapture data. Reference priors are developed for such model and sampling-based approach through Gibbs sampler is used for inference from posterior distributions. Furthermore approximate Bayes factors are obtained for model selection between trap and nontrap response models. Finally one methodology is implemented for a capture-recapture model in generated data and real data.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.18-23
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• 2008

In this paper, we propose the input image selection-method to improve the reconstructed high-resolution (HR) image quality. To obtain ideal super-resolution (SR) reconstruction image, all input images are well-registered. However, the registration is not ideal in practice. Due to this reason, the selection of input images with low registration error (RE) is more important than the number of input images in order to obtain good quality of a HR image. The suitability of a candidate input image can be determined by using statistical and restricted registration properties. Therefore, we propose the proper candidate input Low Resolution(LR) image selection-method as a pre-processing for the SR reconstruction in automatic manner. In video sequences, all input images in specified region are allowed to use SR reconstruction as low-resolution input image and/or the reference image. The candidacy of an input LR image is decided by the threshold value and this threshold is calculated by using the maximum motion compensation error (MMCE) of the reference image. If the motion compensation error (MCE) of LR input image is in the range of 0 < MCE < MMCE then this LR input image is selected for SR reconstruction, else then LR input image are neglected. The optimal reference LR (ORLR) image is decided by comparing the number of the selected LR input (SLRI) images with each reference LR input (RLRI) image. Finally, we generate a HR image by using optimal reference LR image and selected LR images and by using the Hardie's interpolation method. This proposed algorithm is expected to improve the quality of SR without any user intervention.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.4
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• pp.451-463
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• 2023

With South Korea increasingly focusing on nuclear energy, the management of spent nuclear fuel has attracted considerable attention in South Korea. This study established a novel procedure for selecting safety-relevant radionuclides for long-term safety assessments of a deep geological repository in South Korea. Statistical evaluations were performed to identify the design basis reference spent nuclear fuels and evaluate the source term for up to one million years. Safety-relevant radionuclides were determined based on the half-life criteria, the projected activities for the design basis reference spent nuclear fuel, and the annual limit of ingestion set by the Nuclear Safety and Security Commission Notification No. 2019-10 without considering their chemical and hydrogeological properties. The proposed process was used to select 56 radionuclides, comprising 27 fission and activation products and 29 actinide nuclides. This study explains first the determination of the design basis reference spent nuclear fuels, followed by a comprehensive discussion on the selection criteria and methodology for safety-relevant radionuclides.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.551-566
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• 2006

In this paper, we consider a Bayesian model selection for the intraclass correlation coefficient in familiar data. In particular, we compare two nested models such as the independence and intraclass models using the reference prior. A criterion for testing is the Bayesian Reference Criterion by Bernardo (1999) and the Intrinsic Bayes Factor by Berger and Pericchi (1996). We provide numerical examples using simulation data sets for illustration.

• Journal of the Korean Statistical Society
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• v.11 no.1
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• pp.12-24
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• 1982

Selection procedures are proposed for selecting the 'best' industrial process with the smallest fraction defective. For normally distributed industrial processes, this is equivalent to selecting in terms of coefficients of variation. For the case of known vairances, selection procedures by Bechhofer (1954), and Bechhofer and Turnball (1978) are appropriate. We treat this problem for the case of uknown variances with or without reference to a standard. The large sample solutions of design constants are tabulated and the performance of these approximate solutions are investigated.

• Journal of Microbiology and Biotechnology
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• v.27 no.1
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• pp.112-121
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• 2017

Edwardsiella tarda is a gram-negative pathogenic bacterium in aquaculture that can cause hemorrhagic septicemia in fish. Many secreted proteins have already been identified as virulent factors of E. tarda. Moreover, since virulent phenotypes are based on the expression regulation of virulent genes, understanding the expression profile of virulent genes is important. A quantitative RT-PCR is one of the preferred methods for determining different gene expressions. However, this requires the selection of a stable reference gene in E. tarda, which has not yet been systematically studied. Accordingly, this study evaluated nine candidate reference genes (recA, uup, rpoB, rho, topA, gyrA, groEL, rpoD, and 16S rRNA) using the Excel-based programs BestKeeper, GeNorm, and NormFinder under different culture conditions. The results showed that 16S rRNA was more stable than the other genes at different culture growth phases. However, at the same culture time, topA was identified as the reference gene under the conditions of different strains, different culture media, and infection, whereas gyrA was identified under the condition of different temperatures. Thus, in experiments, the expression of gapA and fbaA in E. tarda was analyzed by RT-qPCR using 16S rRNA, recA, and uup as the reference genes. The results showed that 16S rRNA was the most suitable reference gene in this analysis, and that using unsuitable reference genes resulted in inaccurate results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3A
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• pp.325-333
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• 2000

The proposed RPSS(Reference Picture Segment Selection) mode is the RPS mode in picture segment of the ISD mode. The RPS mode has the weakness that it has to change the whole reference picture even if transmission error occurs only in the small part of picture. If the RPS mode is applied only to an error-occurred part and a conventional coding scheme is applied to an error-free part, the higher coding efficiency can be obtained. Simulation results show that there is the optimal number of segment which provides that best performance with given environment such as the BER(Bit Error Rate) of wireless channels, the characteristics of imput sequence, what kind of RPSS mode is used, etc. To apply the channel-adoptive RPSS mode later, the scheme which can change the number of segment without INTRA refresh and spatial error propagation is proposed in this paper.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.8-13
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• 2001

In the turning process, the feed is usually selected by a machining operator considering workpiece, cutting tool and depth of cut. Even if this selection can avoid power saturation or tool breakage, it is usually conservative compared to the capacity of the machine tools and can reduce the productivity significantly. This paper proposes a selection method of the feed and the reference cutting force based on MRR(material removal rate), maximum spindle power and specific energy. In order to estimate and control cutting force accurately in transient and steady state, this study utilizes a synthesized cutting force estimation method and a Fuzzy controller. The experimental results present that these systems can be useful for the FMS(flexible manufacturing system) and unmanned automation system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.7
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• pp.1446-1452
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• 2002

In the turning process, the feed is usually selected by a machining operator considering workpiece, cutting tool and depth of cut. Even if this selection can avoid power saturation or tool breakage, it is usually conservative compared to the capacity of the machine tools and can reduce the productivity significantly. This paper proposes a selection method of the feed and the reference cutting force based on MRR(material removal rate), maximum spindle power and specific energy. In order to estimate and control cutting force accurately in transient and steady state, this study utilizes a synthesized cutting force estimation method and a Fuzzy controller. The experimental results show that these systems can be useful for the unmanned turning process.