• Kyungpook Mathematical Journal
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• 제52권4호
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• pp.413-431
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• 2012

Let $C^r[0,t]$ be the function space of the vector-valued continuous paths $x:[0,t]{\rightarrow}\mathbb{R}^r$ and define $X_t:C^r[0,t]{\rightarrow}\mathbb{R}^{(n+1)r}$ and $Y_t:C^r[0,t]{\rightarrow}\mathbb{R}^{nr}$ by $X_t(x)=(x(t_0),\;x(t_1),\;{\cdots},\;x(t_{n-1}),\;x(t_n))$ and $Y_t(x)=(x(t_0),\;x(t_1),\;{\cdots},\;x(t_{n-1}))$, respectively, where $0=t_0$ < $t_1$ < ${\cdots}$ < $t_n=t$. In the present paper, using two simple formulas for the conditional expectations over $C^r[0,t]$ with the conditioning functions $X_t$ and $Y_t$, we establish evaluation formulas for the analogue of the conditional analytic Fourier-Feynman transform for the function of the form $${\exp}\{{\int_o}^t{\theta}(s,\;x(s))\;d{\eta}(s)\}{\psi}(x(t)),\;x{\in}C^r[0,t]$$ where ${\eta}$ is a complex Borel measure on [0, t] and both ${\theta}(s,{\cdot})$ and ${\psi}$ are the Fourier-Stieltjes transforms of the complex Borel measures on $\mathbb{R}^r$.

• 대한수학회보
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• 제48권3호
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• pp.655-672
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• 2011

Let $C^r$[0,t] be the function space of the vector-valued continuous paths x : [0,t] ${\rightarrow}$ $R^r$ and define $X_t$ : $C^r$[0,t] ${\rightarrow}$ $R^{(n+1)r}$ and $Y_t$ : $C^r$[0,t] ${\rightarrow}$ $R^{nr}$ by $X_t(x)$ = (x($t_0$), x($t_1$), ..., x($t_{n-1}$), x($t_n$)) and $Y_t$(x) = (x($t_0$), x($t_1$), ..., x($t_{n-1}$)), respectively, where 0 = $t_0$ < $t_1$ < ... < $t_n$ = t. In the present paper, with the conditioning functions $X_t$ and $Y_t$, we introduce two simple formulas for the conditional expectations over $C^r$[0,t], an analogue of the r-dimensional Wiener space. We establish evaluation formulas for the analogues of the analytic Wiener and Feynman integrals for the function $G(x)=\exp{{\int}_0^t{\theta}(s,x(s))d{\eta}(s)}{\psi}(x(t))$, where ${\theta}(s,{\cdot})$ and are the Fourier-Stieltjes transforms of the complex Borel measures on ${\mathbb{R}}^r$. Using the simple formulas, we evaluate the analogues of the conditional analytic Wiener and Feynman integrals of the functional G.

• 대한간호
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• 제33권3호
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• pp.79-91
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• 1994

The purpose of this study was to identify the meaningful nursing diagnosis in maternity unit and to suggest formally the basal data to the nursing service with scientific approach. The subject for this paper were 64 patients who admitted to Chung Ang University Hospital, Located in Seoul, from Mar. 10, to July 21, 1993. The results were as follows: 1. The number of nursing diagnosis from 64 patients were 892 and average number of nursing diagnosis per patient was 13.9. 2. Applying the division of nursing diagnosis to Roy's Adaptation Model, determined nursing diagnosis from the 64 patients were 621 (69.6%) in physiological adaptation mode and (Comfort, altered r/t), (Injury, potential for r/t), (Infection, potential for r/t), (Bowel elimination, altered patterns r/t), (Breathing pattern, ineffective r/t), (Nutrition, altered r/t less than body requirement) in order, and 139 (15.6%) in role function mode, (Self care deficit r/t), (Knowledge deficit r/t), (Mobility, impaired physical r/t) in order, 122 (13.7%) in interdependence adaptation mode, (Anxiety r/t), (Family Process, altered r/t) in order, 10(1.1%) in self concept adaptation mode, (Powerlessness r/t), (Grieving, dysfunctional r/t) in order. 3. Nursing diagnosis in maternity unit by the medical diagnosis, the average hospital dates were 3.8 days in normal delivery and majority of used nursing diagnosis, (Comfort, altered r/t) 64.6%, (Self care deficit r/t) 13.6% in order, and the average hospital dates were 9.6 days in cesarean section delivery and majority of used nursing diagnosis, (Comfort, altered r/t) 51.6%, (Self care deficit r/t) 15.2%, (Infection, potential for r/t) 9.9%, (Injury, potential "for r/t) 8.1%, (Anxiety r/t) 5.0%, (Mobility, impaired physical r/t) 3.3% in order, and the average hospital dates were 15.8days in preterm labor and majority of used nursing diagnosis, (Comfort, altered r/ t), (Anxiety r/t), (Injury, potential for r/t) in order, and the average short-term hospital dates were 2.5days, long-term hospital dates were 11.5days in gynecologic diseases and majority of used nursing diagnosis, (Comfort, altered r/t). (Self care deficit r/t), (Injury, potential for r/t), (Infection, potential for r/t) in order.

• 대한수학회지
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• 제32권4호
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• pp.725-737
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• 1995

Let $X_t = (X_t^(1), X_t^(2))', t \geqslant 0$, be a real stationary 2-dimensional Gaussian process with $EX_t^(1) = EX_t^(2) = 0$ and $$ EX_0 X'_t = (_{\rho(t) r(t)}^{r(t) \rho(t)}), $$ where $r(t) \sim $\mid$t$\mid$^-\alpha, 0 < \alpha < 1/2, \rho(t) = o(r(t)) as t \to \infty, r(0) = 1, and \rho(0) = \rho (0 \leqslant \rho < 1)$. For $t > 0, u > 0, and \upsilon > 0, let L_t (u, \upsilon)$ be the time spent by $X_s, 0 \leqslant s \leqslant t$, above the level $(u, \upsilon)$.

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2002년도 제7차 학술대회 초록집
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• pp.102-102
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• 2002

목적：$\Delta{R}_1$과 $\Delta{R}_2\;^{*}$은 $T_1$, $T_2\;^{*}$로부터 직접 구해야 하지만, 시간 해상도 때문에 각각 $T_1$, $T_2\;^{*}$ 강조영상으로부터 구하는 것이 일반적이다. $T_1$, $T_2\;^{*}$ 강조영상으로부터 얻은 $\Delta{R}_1$과 $\Delta{R}_2\;^{*}$ 과 이중 경사 자장에코 펄스열로부터 얻은 $\Delta{R}_1$과 $\Delta{R}_2\;^{*}$ 를 컴퓨터 가상 실험을 통해서 비교한다. 강조 영상의 신호 세기만으로는 정확한 관류 정보를 얻을 수 없음을 보이고자 한다. 대상 및 방법： 알려진 $\Delta{R}_1$과 $\Delta{R}_2\;^{*}$ 값을 이용하여 강조영상으로부터 구할 수 있는 $\DeltaR_1$과 $\Delta{R}_2\;^{*}$ 을 농도에 따라서 가상실험으로 구하고, 이 값과 이중 경사 자장 에코 펄스열로부터 구할 수 있는 $\Delta{R}_1$과 $\Delta{R}_2\;^{*}$를 가상실험으로 구해서 비교한다.

• Korean Journal of Mathematics
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• 제25권1호
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• pp.1-18
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• 2017

In this paper, we introduce the concepts of ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preclosed sets and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preopen sets in the interval-valued intuitionistic smooth topological space and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized pre-continuous mappings and then investigate some of their properties.

• 한국방사선학회논문지
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• 제11권5호
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• pp.343-351
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• 2017

최신 영상 기법인 MAGiC sequence의 RF coil channel 수 변화에 따른 T1, T2 이완 시간 및 T1, T2 이완율을 측정하여 분석하였고 그에 따른 재현성을 평가하였다. Channel 수가 각각 (1, 8, 16, 32)channel 인 RF coil에 조영제 phantom(1.0, 0.6, 0.2, 0mM)을 위치시키고 MAGiC sequence를 이용하여 T1, T2, R1, R2 map을 획득하였다. 그리고 각각의 channel 수와 농도별로 T1, T2, R1, R2 value 그리고 relaxation rate를 측정하였고 이를 기반으로 각 농도에 따른 Relaxivity를 구하였다. 각각의 coil에서 T1, T2, R1, R2 value를 측정한 결과 T1, R1 value는 coil간의 유의한 차이가 없었다(p>0.05). 하지만 T2, R2 value는 유의한 차이가 있는 것으로 나타났다(p<0.05). 사후분석 결과에서는 T2 value의 경우 1 channel coil에서 측정한 결과가 8, 16, 32 channel coil에서 측정한 결과와 유의한 차이가 나타났고(p<0.05) 8, 16, 32 channel coil간의 차이는 나타나지 않았다(p>0.05). R2 value의 경우도 마찬가지로 1 channel coil에서 측정한 결과가 8, 16, 32 channel coil에서 측정한 결과와 유의한 차이가 나타났으며 또한 8 channel coil에서 측정한 결과와 16 channel coil에서 측정한 결과가 유의한 차이가 나타났다(p<0.05). 결론적으로 T1, R1 value는 coil의 channel 수 변화에 따른 차이가 크지 않지만 T2, R2 value는 큰 차이를 나타냈다. 따라서 MAGiC sequence를 이용하여 T2, R2 value를 정량적으로 측정할 경우 재현성을 위해 동일한 channel 수의 coil을 사용해야 할 것으로 사료된다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제11권1호
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• pp.13-30
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• 2007

In this paper we study the numerical solutions of the stochastic functional differential equations of the following form $$du(x,\;t)\;=\;f(x,\;t,\;u_t)dt\;+\;g(x,\;t,\;u_t)dB(t),\;t\;>\;0$$ with initial data $u(x,\;0)\;=\;u_0(x)\;=\;{\xi}\;{\in}\;L^p_{F_0}\;([-{\tau},0];\;R^n)$. Here $x\;{\in}\;R^n$, ($R^n$ is the ${\nu}\;-\;dimenional$ Euclidean space), $f\;:\;C([-{\tau},\;0];\;R^n)\;{\times}\;R^{{\nu}+1}\;{\rightarrow}\;R^n,\;g\;:\;C([-{\tau},\;0];\;R^n)\;{\times}\;R^{{\nu}+1}\;{\rightarrow}\;R^{n{\times}m},\;u(x,\;t)\;{\in}\;R^n$ for each $t,\;u_t\;=\;u(x,\;t\;+\;{\theta})\;:\;-{\tau}\;{\leq}\;{\theta}\;{\leq}\;0\;{\in}\;C([-{\tau},\;0];\;R^n)$, and B(t) is an m-dimensional Brownian motion.

• 대한수학회논문집
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• 제12권2호
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• pp.393-401
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• 1997

Let $A_1,A_2,\cdots,A_m$ and $B_1,B_2,\cdots,B_n$ be two sequences of events on a given probability space. Let $X_m$ and $Y_n$, respectively, be the number of those $A_i$ and $B_j$, which occur we establish new upper and lower bounds on the probability $P(X=r, Y=t)$ which improve upper bounds and classical lower bounds in terms of the bivariate binomial moment $S_{r,t},S_{r+1,t},S_{r,t+1}$ and $S_{r+1,t+1}$.

• 충청수학회지
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• 제26권2호
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• pp.323-342
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• 2013

Let $C[0,t]$ denote the function space of all real-valued continuous paths on $[0,t]$. Define $Xn:C[0,t]{\rightarrow}\mathbb{R}^{n+1}$ and $X_{n+1}:C[0,t]{\rightarrow}\mathbb{R}^{n+2}$ by $X_n(x)=(x(t_0),x(t_1),{\cdots},x(t_n))$ and $X_{n+1}(x)=(x(t_0),x(t_1),{\cdots},x(t_n),x(t_{n+1}))$, where $0=t_0$ < $t_1$ < ${\cdots}$ < $t_n$ < $t_{n+1}=t$. In the present paper, using simple formulas for the conditional expectations with the conditioning functions $X_n$ and $X_{n+1}$, we evaluate the $L_p(1{\leq}p{\leq}{\infty})$-analytic conditional Fourier-Feynman transforms and the conditional convolution products of the functions which have the form $${\int}_{L_2[0,t]}{{\exp}\{i(v,x)\}d{\sigma}(v)}{{\int}_{\mathbb{R}^r}}\;{\exp}\{i{\sum_{j=1}^{r}z_j(v_j,x)\}dp(z_1,{\cdots},z_r)$$ for $x{\in}C[0,t]$, where $\{v_1,{\cdots},v_r\}$ is an orthonormal subset of $L_2[0,t]$ and ${\sigma}$ and ${\rho}$ are the complex Borel measures of bounded variations on $L_2[0,t]$ and $\mathbb{R}^r$, respectively. We then investigate the inverse transforms of the function with their relationships and finally prove that the analytic conditional Fourier-Feynman transforms of the conditional convolution products for the functions, can be expressed in terms of the products of the conditional Fourier-Feynman transforms of each function.