• Title/Summary/Keyword: T subset

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Nonlinear semigroups on locally convex spaces

  • Hyeon, Son-Kuk
    • East Asian mathematical journal
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    • v.6 no.1
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    • pp.111-121
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    • 1990
  • Let E be a locally convex Hausdorff space and let $\Gamma$ be a calibration for E. In this note we proved that if E is sequentially complete and a multi-vaiued operaturA in E is $\Gamma$-accretive such that $D(A){\subset}Re$ (I+$\lambda$A) for all sufficiently small positive $\lambda$, then A generates a nonlinear $\Gamma$-contraction semiproup {T(t) ; t>0}. We also proved that if E is complete, $Gamma$ is a dually uniformly convex calibration, and an operator A is m-$\Gamma$-accretive, then the initial value problem $$\{{\frac{d}{dt}u(t)+Au(t)\;\ni\;0,\;t >0,\atop u(0)=x}\.$$ has a solution $u:[0,\infty){\rightarrow}E$ given by $u(t)=T(t)x={lim}\limit_{n\rightarrow\infty}(I+\frac{t}{n}A)^{-n}x$ each $x{\varepsilon}D(A)$.

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Selection Conditional on Associated Measurements

  • Yeo, Woon-Bang
    • Journal of the Korean Statistical Society
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    • v.12 no.2
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    • pp.110-114
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    • 1983
  • In this paper, a random subset selection procedure for the choice of the k best objects out of n primary measurements $Y_t$ is considered when only the associated measurements $X_t$ are available. In contrast to Yeo and David (1992), where only the ranks of the X's are needed, the present uses the observed X-values. The approach is illustrated numerically when X and Y are bivariate normal and the standard deviation of X is known.

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AN APPLICATION OF THE STRING AVERAGING METHOD TO ONE-SIDED BEST SIMULTANEOUS APPROXIMATION

  • Rhee, Hyang-Joo
    • The Pure and Applied Mathematics
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    • v.10 no.1
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    • pp.49-56
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    • 2003
  • For (equation omitted) be an ordered $\ell$(t)-tuple of numbers in{1,2, …,$\ell$}and let Tt be chosen from a finite composition of orthogonal projections (equation omitted) acting on the normed linear space $C_1$(X) to closed convex subset $S(fi_{j}\;^{t})$ respectively. In this paper, we study the convergence of the sequence (equation omitted) where (equation omitted).

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EXISTENCE OF FUZZY IDEALS WITH ADDITIONAL CONDITIONS IN BCK/BCI-ALGEBRAS

  • Jun, Young-Bae;Park, Chul-Hwan
    • The Pure and Applied Mathematics
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    • v.14 no.3
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    • pp.223-230
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    • 2007
  • We give an answer to the following question: Question. Let S be a subset of [0,1] containing a maximal element m > 0 and let C :=$\{I_{t}\;{\mid}\;t{\in}S\}$ be a decreasing chain of ideals of a BCK/BCI-algebra X. Then does there exists a fuzzy ideal ${\mu}(X)=S\;and\;C_{\mu}=C?$.

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SOME PROPERTIES OF TOEPLITZ OPERATORS WITH SYMBOL μ

  • Kang, Si Ho
    • Journal of the Chungcheong Mathematical Society
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    • v.23 no.3
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    • pp.471-479
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    • 2010
  • For a complex regular Borel measure ${\mu}$ on ${\Omega}$ which is a subset of ${\mathbb{C}}^k$, where k is a positive integer we define the Toeplitz operator $T_{\mu}$ on a reproducing analytic space which comtains polynomials. Using every symmetric polynomial is a polynomial of elementary polynomials, we show that if $T_{\mu}$ has finite rank then ${\mu}$ is a finite linear combination of point masses.

Optimal Rates of Convergence in Tensor Sobolev Space Regression

  • Koo, Ja-Yong
    • Journal of the Korean Statistical Society
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    • v.21 no.2
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    • pp.153-166
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    • 1992
  • Consider an unknown regression function f of the response Y on a d-dimensional measurement variable X. It is assumed that f belongs to a tensor Sobolev space. Let T denote a differential operator. Let $\hat{T}_n$ denote an estimator of T(f) based on a random sample of size n from the distribution of (X, Y), and let $\Vert \hat{T}_n - T(f) \Vert_2$ be the usual $L_2$ norm of the restriction of $\hat{T}_n - T(f)$ to a subset of $R^d$. Under appropriate regularity conditions, the optimal rate of convergence for $\Vert \hat{T}_n - T(f) \Vert_2$ is discussed.

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The role of dendritic cells in tumor microenvironments and their uses as therapeutic targets

  • Kim, Chae Won;Kim, Kyun-Do;Lee, Heung Kyu
    • BMB Reports
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    • v.54 no.1
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    • pp.31-43
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    • 2021
  • Dendritic cells (DC), which consist of several different subsets, specialize in antigen presentation and are critical for mediating the innate and adaptive immune responses. DC subsets can be classified into conventional, plasmacytoid, and monocyte-derived DC in the tumor microenvironment, and each subset plays a different role. Because of the role of intratumoral DCs in initiating antitumor immune responses with tumor-derived antigen presentation to T cells, DCs have been targeted in the treatment of cancer. By regulating the functionality of DCs, several DC-based immunotherapies have been developed, including administration of tumor-derived antigens and DC vaccines. In addition, DCs participate in the mechanisms of classical cancer therapies, such as radiation therapy and chemotherapy. Thus, regulating DCs is also important in improving current cancer therapies. Here, we will discuss the role of each DC subset in antitumor immune responses, and the current status of DC-related cancer therapies.

VARIOUS CONTINUITIES OF A MAP f ; (X, k, TnX) → (Y, 2, TY) IN COMPUTER TOPOLOGY

  • HAN, SANG-EON
    • Honam Mathematical Journal
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    • v.28 no.4
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    • pp.591-603
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    • 2006
  • For a set $X{\subset}{\mathbb{Z}}^n$ let $(X,\;T^n_X)$ be the subspace of the Khalimsky n-dimensional space $({\mathbb{Z}}^n,\;T^n)$, $n{\in}N$. Considering a k-adjacency of $(X,\;T^n_X)$, we use the notation $(X,\;k,\;T^n_X)$. In this paper for a map $$f:(X,\;k,\;T^n_X){\rightarrow}(Y,\;2\;T_Y)$$, we find the condition that weak (k, 2)-continuity of the map f implies strong (k, 2)-continuity of f.

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ESSENTIAL SPECTRA OF ${\omega}-HYPONORMAL$ OPERATORS

  • Cha, Hyung-Koo;Kim, Jae-Hee;Lee, Kwang-Il
    • The Pure and Applied Mathematics
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    • v.10 no.4
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    • pp.217-223
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    • 2003
  • Let $\cal{K}$ be the extension Hilbert space of a Hilbert space $\cal{H}$ and let $\Phi$ be the faithful $\ast$-representation of $\cal{B}(\cal{H})$ on $\cal{k}$. In this paper, we show that if T is an irreducible ${\omega}-hyponormal$ operators such that $ker(T)\;{\subset}\;ker(T^{*})$ and $T^{*}T\;-\;TT^{\ast}$ is compact, then $\sigma_{e}(T)\;=\;\sigma_{e}(\Phi(T))$.

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