In this study,the electronic transition properties and structural analysis of the metal complexes(Ni(Ⅱ),Co(Ⅱ),Cu(Ⅱ)and Mn(Ⅱ))of three different polymer ligands were performed by using XRF and X-ray diffraction(XRD...In this study,the electronic transition properties and structural analysis of the metal complexes(Ni(Ⅱ),Co(Ⅱ),Cu(Ⅱ)and Mn(Ⅱ))of three different polymer ligands were performed by using XRF and X-ray diffraction(XRD)techniques,respectively.The structural analysis of the polymers and their complexes were performed by XRD technique and some of the polymers were found to be in the face-centred cubic(fcc)structure.In addition,the values of the present K X-ray intensity ratios are significantly greater than the values reported in literature.展开更多
Springback of a SUS321 complex geometry part formed by the multi-stage rigid-flexible compound process was studied through numerical simulations and laboratory experiments in this work.The sensitivity analysis was pro...Springback of a SUS321 complex geometry part formed by the multi-stage rigid-flexible compound process was studied through numerical simulations and laboratory experiments in this work.The sensitivity analysis was provided to have an insight in the effect of the evaluated process parameters.Furthermore,in order to minimize the springback problem,an accurate springback simulation model of the part was established and validated.The effects of the element size and timesteps on springback model were further investigated.Results indicate that the custom mesh size is beneficial for the springback simulation,and the four timesteps are found suited for the springback analysis for the complex geometry part.Finally,a strategy for reducing the springback by changing the geometry of the blank is proposed.The optimal blank geometry is obtained and used for manufacturing the part.展开更多
针对复杂电磁环境下雷达复合干扰识别困难和网络模型复杂度高的问题,将多标签分类与改进的ShuffleNet V2相结合,提出一种轻量化的多标签ShuffleNet(multi-labeling ShuffleNet, ML-SNet)雷达复合干扰识别算法。首先,使用轻量化的Shuffle...针对复杂电磁环境下雷达复合干扰识别困难和网络模型复杂度高的问题,将多标签分类与改进的ShuffleNet V2相结合,提出一种轻量化的多标签ShuffleNet(multi-labeling ShuffleNet, ML-SNet)雷达复合干扰识别算法。首先,使用轻量化的ShuffleNet V2作为主干网络,引入SimAM(similarity-based attention module)注意力机制,提高网络特征提取能力。其次,使用漏斗激活线性整流函数(funnel activation rectified linear unit, FReLU)代替线性整流单元(rectified linear unit, ReLU)激活函数,减少特征图的信息损失。最后,使用多标签分类算法对网络输出进行分类,得到识别结果。实验结果表明,在干噪比范围为-10~10 dB的情况下,所提算法对15类雷达复合干扰的平均识别率为97.9%。与其他网络相比,所提算法具有较低的计算复杂度,而且识别性能表现最佳。展开更多
为探究黄河流域复合型灾害的特征及其风险演化模式,首先厘清复合型灾害的基本特征,基于黄河流域2000-2023年的1553条灾害数据,归纳出10种典型的灾害链演化路径。通过构建复合型灾害的复杂网络模型,运用基于节点相似度和标签传播的加权...为探究黄河流域复合型灾害的特征及其风险演化模式,首先厘清复合型灾害的基本特征,基于黄河流域2000-2023年的1553条灾害数据,归纳出10种典型的灾害链演化路径。通过构建复合型灾害的复杂网络模型,运用基于节点相似度和标签传播的加权网络社团划分算法(Weighted Network Community Division Method based on Node Similarity and Label Propagation,SLWCD)对网络节点进行分类,识别影响复合型灾害风险水平的关键节点。结果表明:洪涝灾害为黄河流域复合型灾害网络中的核心节点,具有最强的全局影响力;水污染事故较易受到自然灾害或首发事故的触发,干旱与地震则为黄河流域的高频灾害。聚类分析结果揭示了四类显著的效应机制,分别为:风雨沙灾害与社会安全事件的时空累积效应、各类灾害与公共卫生事件的级联效应、地质灾害与事故灾难的联动效应及土地问题对公共卫生事件的长期影响。此外,通过Python模拟,研究发现黄河流域复合型灾害网络中潜在路径长度大于4的灾害链条共有7646条。基于研究结果,提出了以下政策建议:增强灾害预警与应急响应能力,统筹跨部门协作,强化高风险区域的监测,推进生态保护与可持续发展,优化水资源与污染防控,采取综合适应策略应对气候变化,以有效提升黄河流域应对复合型灾害的能力。展开更多
基金Scientific Research Fund of Kahramanmaras Sutcu Imam University,Turkey(2012/3-7YLS)
文摘In this study,the electronic transition properties and structural analysis of the metal complexes(Ni(Ⅱ),Co(Ⅱ),Cu(Ⅱ)and Mn(Ⅱ))of three different polymer ligands were performed by using XRF and X-ray diffraction(XRD)techniques,respectively.The structural analysis of the polymers and their complexes were performed by XRD technique and some of the polymers were found to be in the face-centred cubic(fcc)structure.In addition,the values of the present K X-ray intensity ratios are significantly greater than the values reported in literature.
基金Project(2014ZX04002041)supported by the National Science and Technology Major Project,ChinaProject(51175024)supported by the National Natural Science Foundation of China
文摘Springback of a SUS321 complex geometry part formed by the multi-stage rigid-flexible compound process was studied through numerical simulations and laboratory experiments in this work.The sensitivity analysis was provided to have an insight in the effect of the evaluated process parameters.Furthermore,in order to minimize the springback problem,an accurate springback simulation model of the part was established and validated.The effects of the element size and timesteps on springback model were further investigated.Results indicate that the custom mesh size is beneficial for the springback simulation,and the four timesteps are found suited for the springback analysis for the complex geometry part.Finally,a strategy for reducing the springback by changing the geometry of the blank is proposed.The optimal blank geometry is obtained and used for manufacturing the part.
文摘针对复杂电磁环境下雷达复合干扰识别困难和网络模型复杂度高的问题,将多标签分类与改进的ShuffleNet V2相结合,提出一种轻量化的多标签ShuffleNet(multi-labeling ShuffleNet, ML-SNet)雷达复合干扰识别算法。首先,使用轻量化的ShuffleNet V2作为主干网络,引入SimAM(similarity-based attention module)注意力机制,提高网络特征提取能力。其次,使用漏斗激活线性整流函数(funnel activation rectified linear unit, FReLU)代替线性整流单元(rectified linear unit, ReLU)激活函数,减少特征图的信息损失。最后,使用多标签分类算法对网络输出进行分类,得到识别结果。实验结果表明,在干噪比范围为-10~10 dB的情况下,所提算法对15类雷达复合干扰的平均识别率为97.9%。与其他网络相比,所提算法具有较低的计算复杂度,而且识别性能表现最佳。
文摘为探究黄河流域复合型灾害的特征及其风险演化模式,首先厘清复合型灾害的基本特征,基于黄河流域2000-2023年的1553条灾害数据,归纳出10种典型的灾害链演化路径。通过构建复合型灾害的复杂网络模型,运用基于节点相似度和标签传播的加权网络社团划分算法(Weighted Network Community Division Method based on Node Similarity and Label Propagation,SLWCD)对网络节点进行分类,识别影响复合型灾害风险水平的关键节点。结果表明:洪涝灾害为黄河流域复合型灾害网络中的核心节点,具有最强的全局影响力;水污染事故较易受到自然灾害或首发事故的触发,干旱与地震则为黄河流域的高频灾害。聚类分析结果揭示了四类显著的效应机制,分别为:风雨沙灾害与社会安全事件的时空累积效应、各类灾害与公共卫生事件的级联效应、地质灾害与事故灾难的联动效应及土地问题对公共卫生事件的长期影响。此外,通过Python模拟,研究发现黄河流域复合型灾害网络中潜在路径长度大于4的灾害链条共有7646条。基于研究结果,提出了以下政策建议:增强灾害预警与应急响应能力,统筹跨部门协作,强化高风险区域的监测,推进生态保护与可持续发展,优化水资源与污染防控,采取综合适应策略应对气候变化,以有效提升黄河流域应对复合型灾害的能力。
