Results 281 to 290 of about 38,177 (303)

Time-Dependent Changes in Performance, Biochemistry, and Histology in Dairy Calves with Acute Aflatoxicosis. [PDF]

Vet Sci
de Luna-López MC, Valdivia-Flores AG, Rangel-Muñoz EJ, Hernández-Valdivia E, Quezada-Tristán T, Jaramillo-Juárez F, Ortiz-Martínez R.   +6 more
europepmc   +1 more source

Concrete Surface Crack Detection Algorithm Based on Improved YOLOv8. [PDF]

Sensors (Basel)
Dong X, Liu Y, Dai J.
europepmc   +1 more source

Utilizing Agro-Waste as Aggregate in Cement Composites: A Comprehensive Review of Properties, Global Trends, and Applications. [PDF]

Materials (Basel)
Netinger Grubeša I, Šamec D, Juradin S, Hadzima-Nyarko M.   +3 more
europepmc   +1 more source

A rough fuzzy kernel clustering algorithm [PDF]

2015 IEEE International Conference on Communication Problem-Solving (ICCP), 2015
Traditional clustering algorithm can't deal with non-linear fuzzy and boundary problem. This paper provides a rough fuzzy kernel clustering algorithm. The algorithm firstly using kernel function map input space to high-dimensional space, make the space can be partitioned linearly.
Zhi Wen Wang, Zhen Jin Huang, Hao Ouyang, Ri Feng Wang   +3 more
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Certain Operators with Rough Singular Kernels

Canadian Journal of Mathematics, 2003
AbstractWe study the singular integral operatordefined on all test functions f, where b is a bounded function, α ≥ 0, Ω (yʻ) is an integrable function on the unit sphere Sn-1 satisfying certain cancellation conditions. We prove that, for 1 < p < ∞, TΩ,α extends to a bounded operator from the Sobolev space to the Lebesgue space Lp with Ω being a ...
Jiecheng Chen, Yiming Ying, Dashan Fan
openaire   +2 more sources

The Kernel Rough K-Means Algorithm

Recent Advances in Computer Science and Communications, 2020
Background: Clustering is one of the most important data mining methods. The k-means (c-means ) and its derivative methods are the hotspot in the field of clustering research in recent years. The clustering method can be divided into two categories according to the uncertainty, which are hard clustering and soft clustering. The Hard C-Means clustering
Dong Zhankui, Wu Zige, Dui Hongyan, Zhou Shiyuan, Wang Meng   +4 more
openaire   +2 more sources

A roughness-penalty view of kernel smoothing

Statistics & Probability Letters, 2001
Abstract It has been shown that a smoothing spline estimate is an equivalent kernel estimate. In this paper, we show that both the Nadaraya–Watson and local linear kernel estimators are equivalent penalized estimators.
Li-Shan Huang, Li-Shan Huang
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Marcinkiewicz integral with rough kernels

Frontiers of Mathematics in China, 2007
In this summary paper, we will introduce some recent progress in the theory of Marcinkiewicz integral and will pay more attention to the case of rough kernels.
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Multilinear Singular Integrals with Rough Kernel

Acta Mathematica Sinica, English Series, 2003
For a class of multilinear singular integral operators T A , $$ T_{A} f{\left( x \right)} = {\int_{\mathbb{R}^{n} } {\frac{{\Omega {\left( {x - y} \right)}}} {{{\left| {x - y} \right|}^{{n + m - 1}} }}} }R_{m} {\left( {A;x,y ...
Huo Xiong Wu, Pu Zhang, Shanzhen Lu
openaire   +2 more sources