• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.113-121
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• 2010

Mixture is that DNA profiles of samples contain material from more than one contributor, especially common in rape cases. In this situation, first, the method based on enumerating a complete set of possible genotype that may have generated the mixed DNA profile have been studied for interpreting DNA mixtures. More recently, the methods utilizing peak area information to calculate likelihood ratios have been suggested. This study is concerned with the analysis and interpretation of mixed forensic stains using quantitative peak area information and the method of forensic inference for extension of material from more than or equal to three contributors. Finally, the numerical example will be outlined.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.47-54
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• 2010

We propose a smart human-computer interface replacing conventional mouse interface. The interface is able to control cursor and command action with only hand performing without object. Four finger motions(left click, right click, hold, drag) for command action are enough to express all mouse function. Also we materialize cursor movement control using image processing. The measure what we use for inference is entropy of EMG signal, gaussian modeling and maximum likelihood estimation. In image processing for cursor control, we use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. we materialize whole system to check its performance and utility.

• Journal of Life Science
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• v.14 no.4
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• pp.593-607
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• 2004

The nucleotide sequence for a nuclear-encoded small subunit rDNA (SSU rDNA) was determined for 43 species of the class Dinophyceae, including harmful algae Cochlodinium polykrikoides and Gyrodinium aureolum. These sequences and data analyses were performed by parsimony, distances and maximum likelihood methods in PHYLIP (Phylogenetic Inference Package) version 3.573c. The species Noctiluca scintillans, Gonyaulax spinifern and Crypthecodinium cohnii occupied a basal position within the Dino- phyceae in our analyses. The genera Alexandrium and Symbiodinium were monophyletic (supported by a bootstrap value of >70%), whereas the genera Gymnedinium and Gyrodinium formed polyphyletic nodes, for which bootstrap support was strong (>70%) in the neighbor-joining and maximum likelihood methods except for the PHYLIP parsimony analysis (=59%). The sequence divergence between G. aureolum and G. dorsum/ G. galathenum was the largest at 7.4% (45 bp), whereas G. aureolum and G. mikimotoi showed an extremely low value of genetic divergence of 0.9% (5 bp). The genetic divergence between C. polykrikoides and G. aureolum was a low value of 5.2% (31 bp). In the phylogenetic analysis, the placement of G. aureolum and C. polykrikoides was closer to the genus Gymnodinium than to the genus Gyrodinium, which was supported by a moderate bootstrap value.

• Molecules and Cells
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• v.27 no.5
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• pp.515-523
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• 2009

To infer the monophyletic origin and phylogenetic relationships of the order Desmoscolecida, a unique and puzzling group of mainly free-living marine nematodes, we newly determined nearly complete 18S rDNA sequences for six marine desmoscolecid nematodes belonging to four genera (Desmoscolex, Greeffiella, Tricoma and Paratricoma). Based on the present data and those of 72 nematode species previously reported, the first molecular phylogenetic analysis focusing on Desmoscolecida was done by using neighbor joining (NJ), maximum parsimony (MP), maximum likelihood (ML) and Bayesian inference (BI) methods. All four resultant trees consistently and strongly supported that the family Desmoscolecidae forms a monophyletic group with very high node confidence values. The monophyletic clade of desmocolecid nematodes was placed as a sister group of the clade including some members of Monhysterida and Araeolaimida, Cyartonema elegans (Cyartonematidae) and Terschellingia Iongicaudata (Linhomoeidae) in all the analyses. However, the present phylogenetic trees do not show any direct attraction between the families Desmoscolecidae and Cyartonematidae. Within the monophyletic clade of the family Desmoscolecidae in all of the present phylogenetic trees, there were consistently observed two distinct subgroups which correspond to the subfamilies Desmoscolecinae [Greeffiella sp. + Desmoscolex sp.] and Tricominae [Paratricoma sp. + Tricoma sp].

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1093-1101
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• 2009

Quantile regression has become a more widely used technique to describe the distribution of a response variable given a set of explanatory variables. This paper proposes a novel modelfor quantile regression using doubly penalized kernel machine with support vector machine iteratively reweighted least squares (SVM-IRWLS). To make inference about the shape of a population distribution, the widely popularregression, would be inadequate, if the distribution is not approximately Gaussian. We present a likelihood-based approach to the estimation of the regression quantiles that uses the asymmetric Laplace density.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.1-8
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• 2009

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. The optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement is generally accepted. The Bayesian parametric inference of model using log Poisson execution time employ tool of Markov chain(Gibbs sampling and Metropolis algorithm). In a numerical example by T1 data was illustrated. make out estimating software optimal release time from the maximum likelihood estimation and Bayesian parametric estimation.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. 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. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.327-344
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• 2011

This study is the first step for us toward improving high school students' capability of statistical inferences, such as obtaining and interpreting the confidence interval on the population mean that is currently learned in high school. We suggest 5 underlying concepts of 'discretion of contingency and inevitability', 'discretion of induction and deduction', 'likelihood principle', 'variability of a statistic' and 'statistical model', those are necessary to appreciate statistical inferences as a reliable arguing tools in spite of its occasional erroneous conclusions. We assume those 5 concepts above are to be gradually developing in their school periods and Korean mathematics textbooks of grades 1-12 were analyzed. Followings were found. For the right choice of solving methodology of the given problem, no elementary textbook but a few high school textbooks describe its difference between the contingent circumstance and the inevitable one. Formal definitions of population and sample are not introduced until high school grades, so that the developments of critical thoughts on the reliability of inductive reasoning could not be observed. On the contrary of it, strong emphasis lies on the calculation stuff of the sample data without any inference on the population prospective based upon the sample. Instead of the representative properties of a random sample, more emphasis lies on how to get a random sample. As a result of it, the fact that 'the random variability of the value of a statistic which is calculated from the sample ought to be inherited from the randomness of the sample' could neither be noticed nor be explained as well. No comparative descriptions on the statistical inferences against the mathematical(deductive) reasoning were found. Few explanations on the likelihood principle and its probabilistic applications in accordance with students' cognitive developmental growth were found. It was hard to find the explanation of a random variability of statistics and on the existence of its sampling distribution. It is worthwhile to explain it because, nevertheless obtaining the sampling distribution of a particular statistic, like a sample mean, is a very difficult job, mere noticing its existence may cause a drastic change of understanding in a statistical inference.