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Titlebook: Computational Science and Its Applications – ICCSA 2018; 18th International C Osvaldo Gervasi,Beniamino Murgante,Yeonseung Ryu Conference p

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發(fā)表于 2025-3-28 15:12:23 | 只看該作者
42#
發(fā)表于 2025-3-28 20:48:25 | 只看該作者
Tianhao Wang,Geng Cui,Guoquan Zheng providers run multiple data centers in various locations to manage and provision the Cloud resources to their customers. More recently, the introduction of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) opens more opportunities in Clouds which enables dynamic and autono
43#
發(fā)表于 2025-3-28 22:54:14 | 只看該作者
Sagittal Translation During Osteotomyplications to concrete problems in the medical and engineering fields. Regarding the first, a procedure will be presented, based on approaches of approximation theory and on algorithms of digital image processing for the diagnosis of aneurysmal diseases; in particular we discuss the extraction of th
44#
發(fā)表于 2025-3-29 04:00:35 | 只看該作者
45#
發(fā)表于 2025-3-29 09:32:12 | 只看該作者
46#
發(fā)表于 2025-3-29 12:01:13 | 只看該作者
https://doi.org/10.1007/978-3-642-70977-7 components is to generate pseudorandom sequences of bits. There is no mathematical foundation on how to construct an NLFSR feedback function with optimal period. In this work, we review the existing NLFSR feedback functions, and propose new functions with optimal periods.
47#
發(fā)表于 2025-3-29 18:59:58 | 只看該作者
48#
發(fā)表于 2025-3-29 20:47:57 | 只看該作者
Ujjwal K. Chowdhury,Lakshmi Kumari Sankhyannce as much elements as possible, considering a model to simulate the propagation of influence in a network. This paper proposes a Genetic Algorithm to optimize the selection of seeds for the Linear Threshold Model (LTM), a widely adopted simulation model for influence propagation, by investigating
49#
發(fā)表于 2025-3-30 00:14:31 | 只看該作者
50#
發(fā)表于 2025-3-30 06:39:44 | 只看該作者
Ahmed M. Afifi,Ziv M. Peled,Jeffrey E. Janisnd proper starting vertices to be used in conjunction with heuristics for bandwidth reductions since the 1970s. This paper reviews the main algorithms for the identification of pseudo-peripheral vertices and selects seven out of these algorithms as potentially being the most promising low-cost metho
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