• Title/Summary/Keyword: n-norm

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Effects of Phytoncide Aromatherapy on Stress, Symptoms of Stress and Heart Rate Variability among Nursing Students (피톤치드 아로마테라피가 간호대학생의 스트레스, 스트레스 증상 및 심박변이도에 미치는 영향)

  • Kim, Chul-Gyu;Cho, Mi-Kyoung;Kim, Jin-Il
    • Journal of Korean Biological Nursing Science
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    • v.14 no.4
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    • pp.249-257
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    • 2012
  • Purpose: The purpose of this study was to examine the effects of phytoncide aromatherapy on stress, symptoms of stress and heart rate variability among nursing students. Methods: This study is a randomized control-group non-synchronized design. The experimental group (n=31) underwent phytoncide aromatherapy for 2 weeks, while the control group (n=31) received placebo therapy. The data were collected using self-administration questionnaires and measurement of heart rate variability (HRV) and analyzed using SPSS WIN 18.0 program. A p value <.05 was considered statistically significant. Results: Total score of stress, individual score of intrapersonal stress, and score of peripheral manifestations in symptoms of stress in the experimental group were significantly lower than those of the control group. All indices of HRV were significantly different between the two groups. LF norm and LF/HF ratio in the experimental group were significantly lower than those of the control group, and HF norm in the experimental group was significantly higher than that of in the control group. Conclusion: Based on these results, it can be suggested that phytoncide aromatherapy was effective in decreasing stress and peripheral manifestations of stress and changing in HRV among nursing students.

COUNTING THE CINTRALIZERS OF SOME FINITE GROUPS

  • Ashrafi, Ali Reza
    • Journal of applied mathematics & informatics
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    • v.7 no.1
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    • pp.115-124
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    • 2000
  • For a finite group G, #Cent(G) denotes the number of cen-tralizers of its clements. A group G is called n-centralizer if #Cent( G) = n. and primitive n-centralizer if #Cent(G) = #Cent(${\frac}{G}{Z(G)$) = n. In this paper we compute the number of distinct centralizers of some finite groups and investigate the structure of finite groups with Qxactly SLX distinct centralizers. We prove that if G is a 6-centralizer group then ${\frac}{G}{Z(G)$${\cong}D_8$,$A_4$, $Z_2{\times}Z_2{\times}Z_2$ or $Z_2{\times}Z_2{\times}Z_2{\times}Z_2$.

RENEWAL AND RENEWAL REWARD THEORIES FOR T-INDEPENDENT FUZZY RANDOM VARIABLES

  • KIM, JAE DUCK;HONG, DUG HUN
    • Journal of applied mathematics & informatics
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    • v.33 no.5_6
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    • pp.607-625
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    • 2015
  • Recently, Wang et al. [Computers and Mathematics with Ap-plications 57 (2009) 1232-1248.] and Wang and Watada [Information Sci-ences 179 (2009) 4057-4069.] studied the renewal process and renewal reward process with fuzzy random inter-arrival times and rewards under the T-independence associated with any continuous Archimedean t-norm. But, their main results do not cover the classical theory of the random elementary renewal theorem and random renewal reward theorem when fuzzy random variables degenerate to random variables, and some given assumptions relate to the membership function of the fuzzy variable and the Archimedean t-norm of the results are restrictive. This paper improves the results of Wang and Watada and Wang et al. from a mathematical per-spective. We release some assumptions of the results of Wang and Watada and Wang et al. and completely generalize the classical stochastic renewal theorem and renewal rewards theorem.

ON THE THREE OPERATOR SPACE STRUCTURES OF HILBERT SPACES

  • Shin, Dong-Yun
    • Communications of the Korean Mathematical Society
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    • v.11 no.4
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    • pp.983-996
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    • 1996
  • In this paper, we show that $\Vert \xi \Vert_r = \Vert \sum_{i \in I}x_i x^*_i \Vert^{\frac{1}{2}}, \Vert \xi \Vert_c = \Vert \sum_{i \in I}x^*_ix_i \Vert^{\frac{1}{2}}$ for $\xi = \sum_{i \in I}x_i e_i$ in $M_n(H)$, that subspaces as Hilbert spaces are subspaces as column and row Hilbert spaces, and that the standard dual of column (resp., row) Hilbert spaces is the row (resp., column) Hilbert spaces differently from [1,6]. We define operator Hilbert spaces differently from [10], show that our definition of operator Hilbert spaces is the same as that in [10], show that subspaces as Hilbert spaces are subspaces as operator Hilbert spaces, and for a Hilbert space H we give a matrix norm which is not an operator space norm on H.

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FOURIER-BESSEL TRANSFORMATION OF MEASURES WITH SEVERAL SPECIAL VARIABLES AND PROPERTIES OF SINGULAR DIFFERENTIAL EQUATIONS

  • Muravnik, A.B.
    • Journal of the Korean Mathematical Society
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    • v.37 no.6
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    • pp.1043-1057
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    • 2000
  • This paper is devoted to the investigation of mixed Fourier-Bessel transformation (※Equations, See Full-text) We apply the method of [6] which provides the estimate for weighted L(sub)$\infty$-norm of the spherical mean of │f│$^2$ via its weighted L$_1$-norm (generally it is wrong without the requirement of the non-negativity of f). We prove that in the case of Fourier-Bessel transformatin the mentioned method provides (in dependence on the relation between the dimension of the space of non-special variables n and the length of multiindex ν) similar estimates for weighted spherical means of │f│$^2$, the allowed powers of weights are also defined by multiindex ν. Further those estimates are applied to partial differential equations with singular Bessel operators with respect to y$_1$, …, y(sub)m and we obtain the corresponding estimates for solutions of the mentioned equations.

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Lindley Type Estimators with the Known Norm

  • Baek, Hoh-Yoo
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.1
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    • pp.37-45
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    • 2000
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\underline{\theta}}(p{\geq}4)$ under the quadratic loss, based on a sample ${\underline{x}_{1}},\;{\cdots}{\underline{x}_{n}}$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\;{\underline{\theta}}\;-\;{\bar{\theta}}{\underline{1}}\;{\parallel}$ is known, where ${\bar{\theta}}=(1/p){\sum_{i=1}^p}{\theta}_i$ and $\underline{1}$ is the column vector of ones.

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Estimators Shrinking towards Projection Vector for Multivariate Normal Mean Vector under the Norm with a Known Interval

  • Baek, Hoh Yoo
    • Journal of Integrative Natural Science
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    • v.11 no.3
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    • pp.154-160
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    • 2018
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-r{\geq}3)$, r = rank(K) with a projection matrix K under the quadratic loss, based on a sample $Y_1$, $Y_2$, ${\cdots}$, $Y_n$. In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is constrain, where K is an idempotent and symmetric matrix and rank(K) = r. It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.

Lindley Type Estimators When the Norm is Restricted to an Interval

  • Baek, Hoh-Yoo;Lee, Jeong-Mi
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1027-1039
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    • 2005
  • Consider the problem of estimating a $p{\times}1$ mean vector $\theta(p\geq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $\cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $\parallel\;{\theta}-\bar{{\theta}}1\;{\parallel}$ is restricted to a known interval, where $bar{{\theta}}=\frac{1}{p}\;\sum\limits_{i=1}^{p}{\theta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

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James-Stein Type Estimators Shrinking towards Projection Vector When the Norm is Restricted to an Interval

  • Baek, Hoh Yoo;Park, Su Hyang
    • Journal of Integrative Natural Science
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    • v.10 no.1
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    • pp.33-39
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    • 2017
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-q{\geq}3)$, $q=rank(P_V)$ with a projection matrix $P_v$ under the quadratic loss, based on a sample $X_1$, $X_2$, ${\cdots}$, $X_n$. We find a James-Stein type decision rule which shrinks towards projection vector when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-P_V{\theta}{\parallel}$ is restricted to a known interval, where $P_V$ is an idempotent and projection matrix and rank $(P_V)=q$. In this case, we characterize a minimal complete class within the class of James-Stein type decision rules. We also characterize the subclass of James-Stein type decision rules that dominate the sample mean.

NON-FRAGILE GUARANTEED COST CONTROL OF UNCERTAIN LARGE-SCALE SYSTEMS WITH TIME-VARYING DELAYS

  • Park, Ju-H.
    • Journal of applied mathematics & informatics
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    • v.9 no.1
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    • pp.61-76
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    • 2002
  • The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.