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21.
Hisatoyo Morinaga Natsumi Ogawa Mayu Sakamoto Hiroshi Morikawa 《Journal of polymer science. Part A, Polymer chemistry》2019,57(24):2466-2473
The thiol‐ene reaction between trans‐limonene oxide (trans‐LO) and ethane‐1,2‐dithiol in the presence of triethylborane affords a bio‐based bis‐functional epoxide (bis‐trans‐LO). The crosslinking reaction of bis‐trans‐LO with branched polyethyleneimine (BPEI; Mn = 600; BPEI600) at a feed ratio of bis‐trans‐LO/BPEI600 = 57/43 (wt/wt) yields the corresponding network polymer with Td10 (10% thermal decomposition temperature) of 304.7 °C in 98% yield. In contrast, negligible amounts of network polymer are obtained by the reaction of bis‐LO (bis‐functional epoxide derived from cis and trans‐LO) and BPEI600 regardless of the feed ratio. The mechanical strengths as measured by direct tensile tests of the network polymers derived from bis‐trans‐LO and BPEI600,1800 (Mn = 600 and 1800) were approximately 16 and 11 times higher than that of bis‐LO and BPEI1800, respectively. The tensile shear strengths of the metal‐to‐metal adhesive bonds induced by bis‐trans‐LO and BPEI600,1800 were 9.5 and 14.1 MPa, respectively. DMA revealed that the storage modulus of the network polymer derived from bis‐trans‐LO and BPEI1800 in the rubber region was higher than that of the material prepared from bis‐LO and BPEI1800, indicating higher crosslink density of the bis‐trans‐LO/BPEI1800 system. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019 , 57, 2466–2473 相似文献
22.
由于AD HOC网络自身的特点,其网络管理很多方面与固定网络不同,如移动性管理和体系结构管理等。讨论了AD HOC网络管理的各个方面,并列举了各个方面的设计思路和已有的相关算法的简介。 相似文献
23.
介绍了数字集群的技术性能和在国外的发展概况,叙述了数字集群通信在我国的使用和发展前景。 相似文献
24.
基于mobile agent的分布式网络自管理模型 总被引:2,自引:1,他引:1
为了解决大规模、异构网络环境下基于“管理员密集”的传统网络管理模式带来的低效率和高出错率问题,提出了一种网络自管理模型,从网络管理的自动初始化和动态自管理两个方面实现对网络自动、自主、自适应的管理;提出了管理定位服务这一关键技术,在多个管理站协同工作的分布式网络环境中为设备自动定位出合适的管理站及初始的管理任务;采用可伸缩的分布式体系结构,适应了大规模网络的规模可变性等特点;基于mobile agent的管理框架进一步提高了管理的自适应性和灵活性。 相似文献
25.
Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a
given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred
to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional
(resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional
(resp., unidirectional) topology is k-edge connected.
The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied
by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18],
which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19],
which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity.
In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity,
and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity
and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for
distributed implementation.
A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless
(Adhoc-Now 2003).
Research performed in part while visiting the Max-Plank-Institut fur Informatik.
Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting
researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University
of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms.
Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor
since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and
Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990.
His research interests include optical networks and wireless networks. 相似文献
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29.
径向基函数神经网络的再学习算法及其应用 总被引:3,自引:1,他引:2
谭建辉 《微电子学与计算机》2006,23(5):115-117,120
为了应用径向基函数神经网络逐步地识别待研究系统,文章针对径向基函数神经网络的再学习算法开展了深入的研究.应用严格的数学推理方法,将径向基函数神经网络的再学习问题转化为矩阵求逆的附加运算.详细给出了径向基函数神经网络再学习算法中增加新训练样本和增加新基函数的数学公式,同时对如何获取新的训练样本进行了研究. 相似文献
30.
目前需求预测在整个印制电路板产业的生产活动控制中正扮演着越来越重要的角色。分析了影响印制电路板需求的因素和现有的预测方法,提出了一种适用于PCB产业需求预测的有效方法——遗传/BP—神经网络。实验表明该方法能够进一步改善印制电路板预测的准确度和减少生产成本的消耗。 相似文献