• Journal of Applied and Pure Mathematics
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• 제4권5_6호
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• pp.269-286
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• 2022

In this article we exhibit univariate and multivariate quantitative approximation by Kantorovich-Choquet type quasi-interpolation neural network operators with respect to supremum norm. This is done with rates using the first univariate and multivariate moduli of continuity. We approximate continuous and bounded functions on ℝ^N , N ∈ ℕ. When they are also uniformly continuous we have pointwise and uniform convergences. Our activation functions are induced by the arctangent, algebraic, Gudermannian and generalized symmetrical sigmoid functions.

• International Journal of Contents
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• 제2권4호
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• pp.8-11
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• 2006

This paper describes several loop partitioning techniques such as loop splitting method by thresholds and Polychronopoulos' loop splitting method for exploiting parallelism from single loop which already developed. We propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences. The algorithms generalize how to transform general single loops into parallel loops.

• International Journal of Contents
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• 제3권3호
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• pp.15-19
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• 2007

We review some loop partitioning techniques such as loop splitting method by thresholds and Polychronopoulos' loop splitting method for exploiting parallelism from single loop which already developed. We propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the iteration and distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences. The algorithms generalize how to transform general single loops with one dependence as well as with multiple dependences into parallel loops.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.1021-1028
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• 2006

We shall propose ML, ordinary jackknife and biased reducing estimators of the parameter in the right truncated exponential distribution with an unidentified uniform outlier when the truncated point is unknown and their biases and MSE's are compared numerically each other in the small sample sizes.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2011년도 제40회 동계학술대회 초록집
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• pp.1-1
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• 2011

We developed a new generalized synthetic procedure, called as "heat-up process," to produce uniform-sized nanocrystals of many transition metals and oxides without a size selection process. We were able to synthesize uniform magnetite nanocrystals as much as 1 kilogram-scale from the thermolysis of Fe-oleate complex. Clever combination of different nanoscale materials will lead to the development of multifunctional nano-biomedical platforms for simultaneous targeted delivery, fast diagnosis, and efficient therapy. In this presentation, I would like to present some of our group's recent results on the designed fabrication of multifunctional nanostructured materials based on uniform-sized magnetite nanoparticles and their medical applications. Uniform ultrasmall iron oxide nanoparticles of <3 nm were synthesized by thermal decomposition of iron-oleate complex in the presence of oleyl alcohol. These ultrasmall iron oxide nanoparticles exhibited good T1 contrast effect. In in vivo T1 weighted blood pool magnetic resonance imaging (MRI), iron oxide nanoparticles showed longer circulation time than commercial gadolinium complex, enabling high resolution imaging. We used 80 nm-sized ferrimagnetic iron oxide nanocrystals for T2 MRI contrast agent for tracking transplanted pancreatic islet cells and single-cell MR imaging. We reported on the fabrication of monodisperse magnetite nanoparticles immobilized with uniform pore-sized mesoporous silica spheres for simultaneous MRI, fluorescence imaging, and drug delivery. We synthesized hollow magnetite nanocapsules and used them for both the MRI contrast agent and magnetic guided drug delivery vehicle.

• Smart Structures and Systems
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• 제18권4호
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• pp.707-731
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• 2016

A unified mathematical model of the equations of generalized magneto-thermoelasticty based on fractional derivative heat transfer for isotropic perfect conducting media is given. Some essential theorems on the linear coupled and generalized theories of thermoelasticity e.g., the Lord- Shulman (LS) theory, Green-Lindsay (GL) theory and the coupled theory (CTE) as well as dual-phase-lag (DPL) heat conduction law are established. Laplace transform techniques are used. The method of the matrix exponential which constitutes the basis of the state-space approach of modern theory is applied to the non-dimensional equations. The resulting formulation is applied to a variety of one-dimensional problems. The solutions to a thermal shock problem and to a problem of a layer media are obtained in the present of a transverse uniform magnetic field. According to the numerical results and its graphs, conclusion about the new model has been constructed. The effects of the fractional derivative parameter on thermoelastic fields for different theories are discussed.

• 대한전자공학회논문지SP
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• 제46권5호
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• pp.8-14
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• 2009

본 논문에서는, 컴프레시브 센싱(compressive sensing, CS)에서 양자화된 측정을 사용하여 CS 복구(reconstruction)를 하는 경우에 일반화된 양자화 제한(generalized quantization constraint, GQC) 집합을 사용하여 convex 최적화를 수행하는 방법을 제안하였다. 제안한 GQC에서는 기존의 양자화 제한 집합의 크기를 조정할 수 있도록 하였으며, 균일 스칼라 양자기를 사용한 CS 복구의 모의실험을 통하여 m/klogn > 2 인 CS 문제에서, 기존의 QC 방법에 비하여 CS 복구의 에러에서 3.4-3.6dB의 성능 개선을 얻을 수 있었다.

• Journal of Applied and Pure Mathematics
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• 제4권3_4호
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• pp.185-209
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• 2022

Here we exhibit multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or ℝ^N, N ∈ ℕ, by the multivariate normalized, quasi-interpolation, Kantorovich type and quadrature type neural network operators. We treat also the case of approximation by iterated operators of the last four types. These approximations are achieved by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the generalized symmetrical sigmoid function. The approximations are point-wise and uniform. The related feed-forward neural network is with one hidden layer.

• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.85-95
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• 2012

In this paper we define extended negative quadrant dependence which is weaker negative quadrant dependence and show conditions for having extended negative quadrant dependence property. We also derive generalized Farlie-Gumbel-Morgenstern uniform distributions that possess the extended quadrant dependence property.

• 호남수학학술지
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• 제6권1호
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• pp.1-12
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• 1984

Let(X, $\Im$) be a probabilistic metric space with a t-norm. Common fixed point theorems and convergence theorems generalizing the results of Ćirić, Fisher, Sehgal, Istrătescu-Săcuiu and others are proved for three mappings P,S,T on X satisfying $F_{Pu, Pv}(qx){\geq}min\left{F_{Su,Tv}(x),F_{Pu,Su}(x),F_{Pv,Tv}(x),F_{Pu,Tv}(2x),F_{Pv,Su}(2x)\right}$ for every $u, v {\in}X$, all x>0 and some $q{\in}(0, 1)$. One of the main results is extended to uniform spaces. Mathematics Subject Classification (1980): 54H25.