• Convergence Security Journal
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• v.11 no.6
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• pp.73-80
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The delayed software S-shaped reliability model applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).

• Journal of Preventive Medicine and Public Health
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• v.29 no.2 s.53
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• pp.255-264
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• 1996

To study reliability and validity of PWI, this newly developed self-administered questionnaire which measures stress, was given to medical students. All respondent(133) were followed 4 weeks later and 92 were retested. Cronbach's $\alpha$ coefficient of data was 0.93. Test-retest reliability measured by Pearson's correlation coefficient was 0.72(P<0.01). Exploratory factor analysis(EFA) performed by principal axis factor method without iteration and by varimax rotation explored 13 principal components(eigenvalues > 1). After exploring 4 factor structure according to previous study results, factor 1 showed good agreement but other factors did not. Confirmatory factor analysis(CFA) showed poor fit of 4 factor model to data. In the further study, it may be considered to model that has unidimensional factor structure.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.829-840
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• 2013

In this paper, we propose a new lung segmentation method for chest x-ray images which can take both global and local properties into account. Firstly, the initial lung segmentation is computed by applying the active shape model (ASM) which keeps the shape of deformable model from the pre-learned model and searches the image boundaries. At the second segmentation stage, we also applied the localizing region-based active contour model (LRACM) for correcting various regional errors in the initial segmentation. Finally, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by a radiologist. The comparison experiments were performed using 5 lung x-ray images. In our experiment, the Dice coefficient with manually segmented area was $95.33%{\pm}0.93%$ for the proposed method. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for a more accurate early diagnosis and prognosis regarding lung cancer in chest x-ray images.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.92-99
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• 2005

In this paper, we present a high-level design methodology applied on a network system-on-a-chip(SOC) using SystemC. The main target of our approach is to get optimum performance parameters for high network address translation(NAT) throughput. The Fast Ethernet media access controller(MAC) and its direct memory access(DMA) controller are modeled with SystemC in transaction level. They are calibrated through the cycle-based measurement of the operation of the real Verilog register transfer language(RTL). The NAT throughput of the model is within $\pm$10% error compared to the output of the real evaluation board. Simulation speed of the model is more than 100 times laster than the RTL. The validated models are used for intensive architecture exploration to find the performance bottleneck in the NAT router.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.1000-1010
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• 2006

This paper proposes a new architecture for DCT-based motion estimation and compensation. Previous methods do riot take sufficient advantage of the sparseness of 2-D DCT coefficients to reduce execution time. We first derive a recursion equation to perform DCT domain motion estimation more efficiently; we then use it to develop a wavefront array processor (WAP) consisting of processing elements. In addition, we show that the recursion equation enables motion predicted images with different frequency bands, for example, from the images with low frequency components to the images with low and high frequency components. The wavefront way Processor can reconfigure to different motion estimation algorithms, such as logarithmic search and three step search, without architectural modifications. These properties can be effectively used to reduce the energy required for video encoding and decoding. The proposed WAP architecture achieves a significant reduction in computational complexity and processing time. It is also shown that the motion estimation algorithm in the transform domain using SAD (Sum of Absolute Differences) matching criterion maximizes PSNR and the compression ratio for the practical video coding applications when compared to tile motion estimation algorithm in the spatial domain using either SAD or SSD.

• Convergence Security Journal
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• v.13 no.1
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• pp.71-78
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• 2013

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The doubly bounded power law distribution model makeup Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• Convergence Security Journal
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• v.11 no.1
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• pp.25-32
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R_{sq}$.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.525-536
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• 2004

Gene expression profile is numerical data of gene expression level from organism, measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify disease with gene expression profile. Because all genes are not related to disease, it is needed to select related genes that is called feature selection, and it is needed to classify selected genes properly. This paper Proposes GA based method for searching optimal ensemble of feature-classifier pairs that are composed with seven feature selection methods based on correlation, similarity, and information theory, and six representative classifiers. In experimental results with leave-one-out cross validation on two gene expression Profiles related to cancers, we can find ensembles that produce much superior to all individual feature-classifier fairs for Lymphoma dataset and Colon dataset.

• Korean Journal of Child Education & Care
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• v.19 no.1
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• pp.117-127
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• 2019

Objective: The purpose of this study was a teacher efficacy scale for pre-service teacher and to examine the reliability and validity of the scale. Methods: Participants for this study were 428 pre-service teachers from G region. the data were analyzed using correlation, Cronbach's ${\alpha}$, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Results: The pre-service teacher efficacy scale was consisted of 3 factors, 'efficacy for instructional strategies', 'efficacy for student engagement' and 'efficacy for classroom management' with 12 items. Cronbach's ${\alpha}$ was ranged from .72 to .82. The confirmatory factor analysis revealed that CMIN/DF = 1.59, RMSEA = .05, SRMR = .05, TLI = .96, CFI = .97. Conclusion/Implications: In conclusion, all these results show that the pre-service teacher efficacy scale is quite a reliability and validity.