• Journal of The Korean Astronomical Society
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• v.47 no.1
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• pp.1-13
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• 2014

We analyze the dependence of disk morphology (arm class, Hubble type, bar type) of nearby spiral galaxies on the galaxy environment by using local background density (${\Sigma}_n$), projected distance ($r_p$), and tidal index (T I) as measures of the environment. There is a strong dependence of arm class and Hubble type on the galaxy environment, while the bar type exhibits a weak dependence with a high frequency of SB galaxies in high density regions. Grand design fractions and early-type fractions increase with increasing ${\Sigma}_n$, $1/r_p$, and T I, while fractions of flocculent spirals and late-type spirals decrease. Multiple-arm and intermediate-type spirals exhibit nearly constant fractions with weak trends similar to grand design and early-type spirals. While bar types show only a marginal dependence on ${\Sigma}_n$, they show a fairly clear dependence on $r_p$ with a high frequency of SB galaxies at small $r_p$. The arm class also exhibits a stronger correlation with $r_p$ than ${\Sigma}_n$ and T I, whereas the Hubble type exhibits similar correlations with ${\Sigma}_n$ and $r_p$. This suggests that the arm class is mostly affected by the nearest neighbor while the Hubble type is affected by the local densities contributed by neighboring galaxies as well as the nearest neighbor.

• Communications of the Korean Mathematical Society
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• v.12 no.3
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• pp.743-754
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• 1997

We introduce a class of finite and infinite moving average (MA) sequences of multivariate random vectors exponential marginals. The theory of dependence is used to show that in various cases the class of MA sequences consists of associated random variables. We utilize positive dependence properties to obtain some probability bounds for the multivariate processes.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.677-686
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• 1999

In this paper we introduce a class of moving-average(MA) sequences of multivariate random vectors with geometric marginals. The theory of positive dependence is used to show that in various cases the class of MA sequences consists of associated random variables. We utilize positive dependence properties to obtain weakly probability inequality of the multivariate processes.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.687-698
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• 2007

A normal mixture model with which dependence between classes is incorporated is proposed in order to detect differentially expressed genes. Gene clustering approaches suffer from the high dimensional column of microarray expression data matrix which leads to the over-fit problem. Various methods are proposed to solve the problem. In this paper, use of simple averaging data within each class is proposed to overcome the various problems due to high dimensionality when the normal mixture model is fitted. Some experiments through simulated data set and real data set show its availability in actuality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.383-394
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• 2018

This study analyzed the latent profile for identifying the difference in the dependence on smartphone use among middle school students in the 1st grade using the Korean Children and Youth Panel Survey (KCYPS). From the result of this study, first the latent class was separated according to the type of dependence on smartphone use. Class 1 included the students (from fifth grade in elementary school) whose level of reliance on smartphone use was low. Class 2 was selected as the group whose level of reliance on smartphone was high. Secondly, in comparing class 2 to class 1, it was found that the students who have a high probability of being in class 1 were those whose fathers are high achievers, have high early self-esteem and less age attachment. Thirdly, the students in class 1 had a higher sense of neglect than those in class 2. Furthermore, the self-determination of the students in class 2 mediated the effect of neglect on the adolescents' dependence on smartphone use both directly and indirectly.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.105-113
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• 2000

The representation of a procedural program cannot be applied directly to object oriented program representation consisting of class, object, inheritance, and dynamic binding. Furthermore, preexisting program dependence represented the dependence among statements, but not among variables. That is, it could not solve the problem of which variables make an effect on given variables. Consequently, this study presents the method dependence model representing implementation level information including the dependence among variables in an object oriented program. I also propose implementation-based class testing technique based on the test adequacy criterion of an object-oriented program. Considering inter-data member dependences and a set of axioms for test data adequacy, it generates sequences of methods as test cases which satisfy a flow graph-based testing criterion. For a derived class testing, it considers inheritance relationship and the resuability of the testing information for its parent classes which verified the reduction of test cost through the experiment.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.163-175
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• 2020

We consider a wide class of general weakly-dependent processes, called ψ-weak dependence, which unify almost all weak dependence structures of interest found in statistics under natural conditions on process parameters, such as mixing, association, Bernoulli shifts, and Markovian sequences. For detecting the tail behavior of the weakly dependent processes, change point tests are developed by means of cumulative sum (CUSUM) statistics with the empirical distribution functions of sample extremes. The null limiting distribution is established as a Brownian bridge. Its proof is based on the ψ-weak dependence structure and the existence of the phantom distribution function of stationary weakly-dependent processes. A Monte-Carlo study is conducted to see the performance of sizes and powers of the CUSUM tests in GARCH(1, 1) models; in addition, real data applications are given with log-returns of financial data such as the Korean stock price index.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1805-1816
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• 1999

This paper presents the Module Class Dependency Graph for expressing the dependency relations between classes effectively. The object-oriented language is developed independently at design time, and consists of relationship between classes. Therefore we need to consider these characteristics of independence, and to express effectively the relation of classes which is existed in class hierarchy. In the System Dependence Graph and Class Dependence Graph, the relationship of classes is not expressed. To express the class relationship, we propose the Module Class Dependence Graph, and we verify the effectiveness of this method applying to object constructor, inheritance relationship and dynamic binding. Also, we presents the expressing method of parameter to identify the member data of classes. Using this Module Class Dependency Graph, we can analyze the relationship of module class correctly at design time. This method can be applied to reverse engineering, testing, visualization and other various fields to analyze system.

• Honam Mathematical Journal
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• v.32 no.4
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• pp.689-699
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• 2010

We discuss in this paper the notions of extended negative quadrant dependence and its properties. We study a class of bivariate uniform distributions having extended negative quadrant dependence, which is derived by generalizing the uniform representation of a well-known Farlie-Gumbel-Morgenstern distribution. Finally, we also study the limit behavior on the extended negative quadrant dependence.

• Honam Mathematical Journal
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• v.15 no.1
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• pp.129-136
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• 1993

In this paper we present of a class infinite M A (moving-average) sequences of multivariate random vectors. We use the theory of positive dependence to show that in a variety of cases the classes of M A sequences are associated. We then apply the association to establish some probability bounds and moment inequalities for multivariate processes.