• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.745-758
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• 2005

This paper presents a statistical analysis on the position-specific distributions of amino acid residues in transmembrane proteins. A hidden Markov model segments membrane proteins to produce segmented regions of homogeneous statistical property from variable-length amino acids sequences. These segmented residues are analyzed by using chi-square statistic and relative-entropy in order to find position-specific amino acids. This analysis showed that isoleucine and valine concentrated on the center of membrane-spanning regions, tryptophan, tyrosine and positive residues were found frequently near both ends of membrane.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2251-2258
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• 2012

This study compared the unweighted sample design, frequency weighted sample design and complex sample design to using 2009 Korea National Health and Nutrition Examination Survey in an effort to identify whether or not there is any difference in potential risk factors. Pearson chi-square test and Rao-scott chi-square test were applied to the analytic methods. As a result of analyses, all the variables were overestimated as significant risk factors in case of the unweighted sample design to which only the frequency weights were applied. In addition, there were differences in the confidence levels and results from the simple random sampling analysis and complex sample design to which no weight was applied. It is necessary to carry out the complex sample design rather than the analysis to which the frequency weights are applied, in order to ensure the findings to represent the whole population when our national statistics data is used.

• Herbal Formula Science
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• v.20 no.1
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• pp.133-147
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• 2012

Objectives : This study was intended to understand characteristics of symptoms, oriental medicine prescription and laboratory test results according to elapsed time of stroke. Methods : Through the medical records of 205 stroke inpatients in the oriental medical hospital in the year 2010, we investigated manifested symptoms, administered oriental medicine prescription and clinical pathological examination results. Collected items were classified to depend on stroke types, cerebral infarction and hemorrhage. We analyzed association between manifested symptoms, the oriental medicine prescription, and laboratory test results of stroke patients and elapsed time. Chi-square tests were performed to determine the significance level of association. Results : All symptoms, prescriptions and laboratory test results in cerebral infarction patients were associated with elapsed time. Especially, symptoms, prescriptions and pathological examination results showed very high statistical significance with elapsed time (a symptom; chi-square(df)=164.3(22), p<0.001, prescription; chi-square(df)=93.5(22), p<0.001, and pathological examination results; chi-square(df)=164.3(22), p<0.0004). But in the case of cerebral hemorrhage, there was not statistical significance. Conclusions : The elapsed time of stroke may be an essential requisite in catching symptoms and prescribing for stroke patients in oriental medical treatment.

• International Journal of Contents
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• v.3 no.1
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• pp.1-8
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• 2007

The distributions of the minimum correlated F-variable arises in many applied statistical problems including simultaneous analysis of variance (SANOVA), equality of variance, selection and ranking populations, and reliability analysis. In this paper, negative binomial sampling technique is employed to derive the distributions of the minimum of chi-square variables and hence the distributions of the minimum correlated F-variables. The work presented in this paper is divided in two parts. The first part is devoted to develop some combinatorial identities arised from the negative binomial sampling. These identities are constructed and justified to serve important purpose, when we deal with these distributions or their characteristics. Other important results including cumulants and moments of these distributions are also given in somewhat simple forms. Second, the distributions of minimum, chisquare variable and hence the distribution of the minimum correlated F-variables are then derived within the negative binomial sampling framework. Although, multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of the distributions. The computation methods we adopted are exact and no interpolations are involved.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.644-660
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• 2016

The real-time detection of malware remains an open issue, since most of the existing approaches for malware categorization focus on improving the accuracy rather than the detection time. Therefore, finding a proper balance between these two characteristics is very important, especially for such sensitive systems. In this paper, we present a fast portable executable (PE) malware detection system, which is based on the analysis of the set of Application Programming Interfaces (APIs) called by a program and some technical PE features (TPFs). We used an efficient feature selection method, which first selects the most relevant APIs and TPFs using the chi-square ($KHI^2$) measure, and then the Phi (${\varphi}$) coefficient was used to classify the features in different subsets, based on their relevance. We evaluated our method using different classifiers trained on different combinations of feature subsets. We obtained very satisfying results with more than 98% accuracy. Our system is adequate for real-time detection since it is able to categorize a file (Malware or Benign) in 0.09 seconds.

• Tunnel and Underground Space
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• v.21 no.1
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• pp.50-65
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• 2011

Analysis of correlation and behavior characteristics at elastic wave velocity have studied on Korean rock data after checking population size and Chi-square method. Behavior characteristics are quite different from each rock and mechanical parameters at elastic wave velocity. This study shows it is necessary to analize correlation to rock behavior characteristics for correct answer from natural rock.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• Journal of Sasang Constitutional Medicine
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• v.28 no.1
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• pp.51-56
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• 2016

Objectives This study was to identify the types of errors in the statistical analysis and trends of previous reported papers that used various statistical techniques.Methods We have selected 118 original articles for statistical review from the OASIS(http://oasis.kiom.re.kr) and the Pubmed(http://www.pubmed.gov) in the field of Sasang constitutional medicine. Published year was restricted from 2011 to 2015.Results 1. The ANOVA(25.72%) was the statistic of choice overall, followed by the chi-square test(21.74%), regression analysis(14.13%), t-test(11.59%), and etc. 2. By examining the errors of the statistical methods, there were 42(59.2%) thesis with errors among 71 thesis using ANOVA, 19(31.7%) thesis among 60 thesis using chi-square test, and 35(89.7%) over 39 thesis using regression analysis.Conclusions To improve the quality of Sasang Constitution, the participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.332-336
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• 2009

Functional prediction of unannotated proteins is one of the most important tasks in yeast genomics. Analysis of a protein-protein interaction network leads to a better understanding of the functions of unannotated proteins. A number of researches have been performed for the functional prediction of unannotated proteins from a protein-protein interaction network. A chi-square method is one of the existing methods for the functional prediction of unannotated proteins from a protein-protein interaction network. But, the method does not consider the topology of network. In this paper, we propose a novel method that is able to predict specific molecular functions for unannotated proteins from a protein-protein interaction network. To do this, we investigated all protein interaction DBs of yeast in the public sites such as MIPS, DIP, and SGD. For the prediction of unannotated proteins, we employed a modified chi-square measure based on neighborhood counting and we assess the prediction accuracy of protein function from a protein-protein interaction network.