主要介绍了Python常用模块sys,os,time,random功能与用法,结合实例形式分析了Python模块sys,os,time,random功能、原理、相关模块函数、使用技巧与操作注意事项,需要的朋友可以参考下
2024-03-20 02:41:18 74KB Python time
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一维含时薛定谔方程和Lewenstein模型的比较,杜洪川,胡碧涛,本工作分别利用Lewenstein模型或一维数值求解含时薛定谔方程结合麦克斯韦方程研究了高次谐波和阿秒脉冲的产生。结果表明:对于单体�
2024-03-02 11:07:54 472KB 首发论文
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基于实时子结构加载系统的隔震橡胶支座的动力性能研究,袁涌,朱宏平,本文速度控制型实时子结构加载系统,对天然隔震橡胶支座(NR)、高阻尼隔震橡胶支座(HDR) 和超高阻尼隔震橡胶支座(HDR-S)等速度相关型支座
2024-01-16 10:14:26 1.01MB 首发论文
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通过状态空间方法的时间序列分析
2024-01-14 13:08:42 8.74MB 状态空间方法 时间序列分析
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LPTN | | 实时高分辨率真实感图像翻译:拉普拉斯金字塔翻译网络梁洁*、曾慧*、。 在 CVPR 2021 中。 抽象的 现有的图像到图像转换 (I2IT) 方法要么受限于低分辨率图像,要么由于对高分辨率特征图卷积的计算负担过重而导致推理时间长。 在本文中,我们专注于加速基于封闭形式拉普拉斯金字塔分解和重建的高分辨率逼真 I2IT 任务。 具体来说,我们揭示了属性变换,如光照和颜色处理,更多地与低频分量相关,而内容细节可以在高频分量上自适应地细化。 因此,我们提出了一个拉普拉斯金字塔翻译网络 (LPTN) 来同时执行这两项任务,我们设计了一个轻量级网络,用于翻译分辨率降低的低频分量和渐进式掩蔽策略,以有效地改进高频分量。 我们的模型避免了处理高分辨率特征图所消耗的大部分繁重计算,并忠实地保留了图像细节。 在各种任务上的大量实验结果表明,所提出的方法可以使用一个普通 GPU 实时转换 4
2024-01-12 16:22:31 269KB Python
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三维大气海洋原始方程解在有限时间爆破,王术,郑琳,本文研究了无粘的三维大气海洋原始模型的解在有限时间内爆破的问题。通过构造特解的方法来简化三维模型,然后找到推导出来的简化�
2024-01-10 18:59:29 117KB 首发论文
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扩散卷积循环神经网络:数据驱动的交通预测 这是以下论文中Diffusion Convolutional Recurrent Neural Network的TensorFlow实现: Yaguang Li、Rose Yu、Cyrus Shahabi、Yan Liu,,ICLR 2018。 要求 scipy>=0.19.0 numpy>=1.12.1 熊猫>=0.19.2 皮亚尔 统计模型 张量流>=1.3.0 可以使用以下命令安装依赖项: pip install -r requirements.txt 数据准备 洛杉矶(METR-LA)和湾区(PEMS-BAY)的交通数据文件,即metr-la.h5和pems-bay.h5 ,可以在或,需要放入data/文件夹。 *.h5文件使用HDF5文件格式将数据存储在panads.DataFrame 。 下面是一个例子: 传感器_0 传
2024-01-07 22:17:19 10.14MB time-series
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内容简介  网络应用牵涉到很多专业人土,而网站运维人员必须确保应用的每一部分在其整个生命周期中都能正常工作。当初创公司遭遇了未曾预期的访问流量尖峰,或者当某个新特性导致成熟应用失效时,你就需要这样的专业知识。在这部文章和访谈集中,网站运维老手theo schlossnagle、baron schwartz和alistair croll向这个日新月异的领域提供了他们的真知灼见。你还将学到如何使网站蓬勃发展的秘诀,这是来自·最大规模网站建设者的第一手资料。   ·学习网站运维技能,了解这些技巧来自于经验而非学校教育的原因   ·理解为何从应用程序和基础设施收集统计数据都很重要   ·为数据库架构和规模日益增长带来的隐患考虑通用的处理方法   ·学习如何处理宕机和降级相关的人为因素   ·找到在蜂拥而至的巨大流量后避免灾难的方法   ·问题发生后了解症结所在,防止其再次发生 ·查看全部>>目录foreword preface 1 web operations: the career theo schlossnagle why does web operations have it tough? from apprentice to master conclusion 2 how picnik uses cloud computing: lessons learned justin huff where the cloud fits (and why!) where the cloud doesn't fit (for picnik) conclusion 3 infrastructure and application metrics john aiispaw, with matt massie time resolution and retention concerns locality of metrics collection and storage layers of metrics providing context for anomaly detection and alerts log lines are metrics, too correlation with change management and incident timelines making metrics available to your alerting mechanisms using metrics to guide load-feedback mechanisms a metrics collection system, illustrated: ganglia conclusion 4 continuous deployment eric ries small batches mean faster feedback small batches mean problems are instantly localized small batches reduce risk small batches reduce overhead the quality defenders' lament getting started continuous deployment is for mission-critical applications conclusion 5 infrastructure as code adam jacob service-oriented architecture conclusion 6 monitoring patrick debois story: "the start of a journey" step 1: understand what you are monitoring step 2: understand normal behavior step 3: be prepared and learn conclusion 7 how complex systems fail john aiispaw and richard cook how complex systems fail further reading 8 community management and web operations heather champ and john aiispaw 9 dealing with unexpected traffic spikes brian moon how it all started alarms abound putting out the fire surviving the weekend preparing for the future cdn to the rescue proxy servers ?corralling the stampede streamlining the codebase how do we know it works? the real test lessons learned improvements since then 10 dev and cps collaboration and cooperation paul hammond deployment shared, open infrastructure trust on-call developers avoiding blame conclusion 11 how your visitors feel: user-facing metrics alistair croll and sean power why collect user-facing metrics? what makes a site slow? measuring delay building an sla visitor outcomes: analytics other metrics marketing cares about how user experience affects web cps the future of web monitoring conclusion 12 relational database strategy and tactics for the web baron schwartz requirements for web databases how typical web databases grow the yearning for a cluster database strategy database tactics conclusion 13 how to make failure beautiful: the art and science of postmortems jake loomis the worst postmortem what is a postmortem? when to conduct a postmortem who to invite to a postmortem running a postmortem postmortem follow-up conclusion 14 storage anoop nagwani data asset inventory data protection capacity planning storage sizing operations conclusion 15 nonrelational databases eric florenzano nosql database overview some systems in detail conclusion 16 agile infrastructure andrew clay sharer agile infrastructure so, what's the problem? communities of interest and practice trading zones and apologies conclusion 17 things that go bump in the night (and how to sleep through them) mike christian definitions how many 9s? impact duration versus incident duration datacenter footprint gradual failures trust nobody failover testing monitoring and history of patterns getting a good night's sleep contributors index
2023-11-29 16:23:10 12.12MB web operations 网站运维
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Opening Window Time Ratio (OPW-TR) 的多线程实现 C/C++ 源代码包
2023-11-07 08:03:40 671KB 移动数据管理
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2018 UCR Time Series Classification Archive(UCI时间序列数据集,共包含128个数),可用于时间序列分类任务,解压密码为 someone
2023-10-13 16:22:29 301.53MB 数据集
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