利用python对solid works进行风机叶片的自主开发
创作声明:本文部分内容由AI辅助生成(AIGC),仅供参考
Python内容推荐
Python for Informatics
mocc上面python公开课的参考书,全英文
Python Data Structures and Algorithms [2017]
Python Data Structures and Algorithms by Benjamin Baka English | 30 May 2017 | ASIN: B01IF7NLM8 | 310 Pages | AZW3 | 6.63 MB Key Features A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Book Description Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. What you will learn Gain a solid understanding of Python data structures. Build sophisticated data applications. Understand the common programming patterns and algorithms used in Python data science. Write efficient robust code. About the Author Benjamin Baka works as a software developer and has over 10 years, experience in programming. He is a graduate of Kwame Nkrumah University of Science and Technology and a member of the Linux Accra User Group. Notable in his language toolset are C, C++, Java, Python, and Ruby. He has a huge interest in algorithms and finds them a good intellectual exercise. He is a technology strategist and software engineer at mPedigree Network, weaving together a dizzying array of technologies in combating counterfeiting activities, empowering consumers in Ghana, Nigeria, and Kenya to name a few. In his spare time, he enjoys playing the bass guitar and listening to silence. You can find him on his blog. Table of Contents Python objects, types and expressions Python data types and structures Principles of data structure design Lists and pointer structures Stacks and Queues Trees Hashing and symbol tables Graphs and other algorithms Searching Sorting Selction Algorithms Design Ttechniques and Sstrategies Implementations, applications and tools
ordering-tracker-django:简单的订购跟踪器-在Django框架中创建的项目
订购追踪器 该项目的总体思路是帮助团队进行内部协作,以根据Solid Works cad模型报价/订购所有组件和自定义工具。 我在该项目上的第一个目标是能够在单个页面上显示所有活动订单,并能够在单个订单详细信息页面上查看更多详细信息。 构建这种内部应用程序的主要思想是通过研究真正的应用程序来学习django(用python编写的框架)。 从体系结构的角度出发,开始将应用程序设计为monilite django。 部署计划是使用caprover项目加快部署速度(通过直接链接到github仓库-main分支)。数据也将存储在Postgress的托管数据库上。
SolidWorks二次开发在机械零件设计中的应用与研究
SolidWorks二次开发在机械零件设计中的应用与研究
ThoughtWorks笔试代码
ThoughtWorks笔试代码
Robotic-Hand-controlled-by-different-interfaces:蒂华纳机电工程技术大学的学校项目
机械手由不同的界面控制 蒂华纳技术大学机电工程的10个学期项目。 分配给项目的名称是“由不同接口控制的机械手原型”。 设计了具有12个自由度的3D打印的机械手; 并通过外骨骼,HMI和通过网络摄像头的手势控制进行控制。 学生:Moriancumer Rojas Higuera,RaúlDionicio de la Cruz 推介会 通过网络摄像头通过手势进行控制: 通过将Mediapipe与Python结合使用,可通过网络摄像头对控件进行细化 这种控制的优点是可以使用不同大小的手。 如下面的孩子所见。 机械手抓取带有轻质物体的样品。 抓着重物的机器人手的样本。 机械手抓地力样品,带有精密物体。 外骨骼控制: Solid Works设计了一个外骨骼,并组装了总共95个零件,104个螺钉和12个电位器。 水平和垂直运动,显示12个自由度。 通过外骨骼控制抓取轻型物体的机械手样本
Machine Learning Algorithms
Machine Learning Algorithms by Giuseppe Bonaccorso English | 24 July 2017 | ISBN: 1785889621 | ASIN: B072QBG11J | 360 Pages | AZW3 | 12.18 MB Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the
Mastering Java for Data Science
Mastering Java for Data Science by Alexey Grigorev English | 4 May 2017 | ASIN: B01JLBMHMM | 364 Pages | AZW3 | 2.1 MB Key Features An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Book Description Java is the most popular programming language, according to the TIOBE index, and it is a very typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating Data Science applications: it is fast, has a great set of data processing tools, both built-in and external. What is more, choosing Java for Data Science allows you to easily integrate the solutions with the existent software, and bring Data Science into production with less effort. This book will teach you how to create Data Science applications with Java. First, we will revise the most important things when starting a Data Science application, and then brush up the basics of Java and Machine Learning before diving into more advanced topics.We start with going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn Get a solid understanding of the data processing toolbox available in Java Explore the Data Science ecosystem available in Java Find out how to approach different Machine Learning problems with Java Process unstructured information such as natural language texts or images Create your own search engine Get state-of-the-art performance with XGBoost Learn to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy the Data Science models to production and evaluate their performance About the Author Alexey Grigorev is a skilled data scientist, Machine Learning engineer, and software developer with more than 7 years of professional experience. He started his career as a Java developer working at a number of large and small companies, but after a while, he switched to Data Science. Right now Alexey works as a data scientist at Searchmetrics, wherein his day-to-day job he actively uses Java and Python for data cleaning, data analysis, and modeling. His areas of expertise are Machine Learning and Text Mining, but he also enjoys working on a broad set of problems, which is why he often participates in Data Science competitions on platforms such as kaggle.com. You can connect with Alexey on LinkedIn at https://de.linkedin.com/in/agrigorev.
图片转PDF软件名字太短
将图片转为PDF 。。。。。
RTKlib高精度GPS动态定位函数处理过程整理
源码直接下载地址: https://pan.quark.cn/s/a4b39357ea24 RTKLIB 中高精度 GPS 动态定位的函数及处理流程概述 该资源以 RTKLIB 为基础,归纳了相对定位过程中所使用的函数及相关公式,详细阐述了从数据读取到解算最终结果的各个阶段,涵盖了文件输入、基站位置测算、卫星位置确定、双差观测、卡尔曼滤波以及模糊度辨识等核心原理与公式。 一、函数调用顺序及处理流程 在 RTKLIB 平台内,高精度 GPS 动态定位的函数调用顺序可划分为六个主要阶段:启动主函数 main、启动后处理函数 postpos、处理固定站信息 execses_b、处理移动站信息 execses_r、实施处理步骤 execses 以及函数调用顺序图。 1.1 启动主函数 main 在 RTKLIB 平台中,main 函数作为高精度 GPS 动态定位的起始点。该函数负责调用后处理函数 postpos,并将处理结果输出。 1.2 启动后处理函数 postpos postpos 函数是高精度 GPS 动态定位的核心。该函数负责对固定站信息、移动站信息进行处理以及执行处理步骤。 1.3 处理固定站信息 execses_b execses_b 函数负责处理固定站信息,包括读取固定站观测数据文件、计算固定站位置和速度。 1.4 处理移动站信息 execses_r execses_r 函数负责处理移动站信息,包括读取移动站观测数据文件、计算移动站位置和速度。 1.5 实施处理步骤 execses execses 函数负责执行处理步骤,包括计算固定站位置、卫星位置、双差观测、卡尔曼滤波和模糊度辨识等。 二、数据文件输入 在 RTKLIB 平台中,数据文件输入是高精度 GPS ...
解决McAfee卸载托管模式问题
源码直接下载地址: https://pan.quark.cn/s/8e316ca5c189 ### 关于卸载McAfee时遭遇“无法删除于托管模式”故障的应对策略 #### 异常情况描述 在为客户端设备更换安全防护软件的操作环节中,遭遇了一个特定情况:尽管通过“程序和功能”选项成功移除了“McAfee VirusScan Enterprise”以及“McAfee AntiSpyware Enterprise Module”两个软件包,但在尝试移除“McAfee Agent”时,系统持续显示“在托管状态下无法删除”的提示信息。 #### 异常原因探究 此类故障现象主要源于McAfee安全软件的一个关键组件——CMA(Client Management Agent)。CMA作为一个核心的后台服务,尽管不会出现在“程序和功能”的列表中,但在系统运行期间会占用一个服务端口。当用户试图通过标准方法卸载McAfee Agent时,由于CMA仍在运行状态,因此无法成功完成卸载流程。 #### 解决方案概述 为有效应对这一问题,应遵循以下操作流程: 1. **终止McAfee Framework Manager服务操作**: - 进入“控制面板”界面。 - 转至“管理工具”并打开“服务”应用程序。 - 在服务清单中识别出“MCAFEE FRAMEWORK MANAGER”服务。 - 通过右键选择并执行“停止”操作。若该服务无法被停止,可选择将其设置为“禁用”状态,随后重新启动计算机设备。 2. **运用FrmInst.exe执行强制卸载McAfee Agent操作**: - 定位至McAfee默认安装路径下的“Common Framework”文件夹,通常路径为`C:\Progra...
同步电机与构网型变流器的频率稳定特性及多时间尺度交互机理研究(Simulink仿真实现)
内容概要:本文围绕同步电机与构网型变流器在电力系统中的频率稳定特性及其多时间尺度交互机理展开深入研究,重点通过Simulink仿真实现对两者动态响应特性的精确建模与分析。研究系统揭示了同步电机与构网型变流器在不同时间尺度下的频率响应机制,阐明了二者在系统扰动下的动态交互规律,特别是其在惯量支撑、频率调节和暂态稳定性方面的协同与竞争关系。文中构建了高保真的仿真模型,设计了典型运行工况,通过对比分析验证了构网型变流器在提升高比例新能源电力系统频率稳定性方面的潜力与面临的挑战,并提出了针对性的优化控制策略,为现代电力系统的稳定运行提供了坚实的理论支撑与有效的技术路径。; 适合人群:具备电力系统分析、自动控制理论及Simulink仿真基础的研究生、科研人员及从事新能源并网、电力电子与电网稳定研究的工程技术人员。; 使用场景及目标:①用于深入理解同步电机与构网型变流器的动态交互机理;②为高比例电力电子化电力系统的频率稳定分析与控制策略设计提供高精度的仿真验证平台;③服务于相关领域的教学演示、前沿课题研究与工程项目前期论证。; 阅读建议:阅读时应紧密结合Simulink模型文件,重点关注模型搭建的逻辑架构、关键参数的设置依据与仿真结果的内在关联,建议动手复现关键仿真场景,以深化对多时间尺度动态过程的理解,并可在现有模型基础上进行控制策略的改进与拓展性研究。
openssl and openssh upgrade operations (Linux)
源码下载地址: https://pan.quark.cn/s/4ec69e4c2aa4 OpenSSL 以及 OpenSSH 的升级过程(Linux 环境) OpenSSL 和 OpenSSH 是在 Linux 操作系统中扮演关键角色的两个组件,分别承担着加密任务和安全 shell 连接的职责。鉴于技术的不断进步和漏洞的持续曝出,对 OpenSSL 和 OpenSSH 进行升级已经变得十分紧迫。本说明将详尽阐述如何将 OpenSSL 和 OpenSSH 升级至最新版本,以此来保障 Linux 操作系统的安全防护。 升级 zlib 在对 OpenSSL 和 OpenSSH 执行升级之前,必须先行升级 zlib,以保障 OpenSSL 和 OpenSSH 的顺利部署。以下为升级 zlib 的操作步骤: 1. 将 zlib 的安装文件传输至服务器:`pscp C:\Users\ems\zlib-1.2.11.tar.gz root@11.13.0.106:/root/` 2. 对 zlib 的安装文件进行解压缩:`tar zxvf zlib-1.2.11.tar.gz` 3. 转移至 zlib 的目录:`cd zlib-1.2.11` 4. 执行 zlib 的配置操作:`../configure` 5. 编译 zlib:`make` 6. 安装 zlib:`make install` 升级 OpenSSL 在进行 OpenSSL 的升级工作之前,需要确认当前安装的版本是否为最新。如果不是最新版本,则需下载最新版本并执行升级。以下是 OpenSSL 升级的详细步骤: 1. 将 OpenSSL 的安装文件传输至服务器:`pscp C:\Users\ems\openssl-...
如何利用AI技术提升科研院所知识产权管理水平?有哪些实用工具?.docx
科易网基于40亿+科创知识图谱数据库,深度探索AI技术在技术转移、成果转化、技术经纪、知识产权、产业创新、科技招商等垂直领域的多样化应用场景,研究科技创新领域的AI+数智化解决方案,推动科技创新与产业创新智能化发展。
如何提高高校科技成果转化效率?.docx
科易网基于40亿+科创知识图谱数据库,深度探索AI技术在技术转移、成果转化、技术经纪、知识产权、产业创新、科技招商等垂直领域的多样化应用场景,研究科技创新领域的AI+数智化解决方案,推动科技创新与产业创新智能化发展。
如何高效匹配高校与企业技术合作?.docx
科易网基于40亿+科创知识图谱数据库,深度探索AI技术在技术转移、成果转化、技术经纪、知识产权、产业创新、科技招商等垂直领域的多样化应用场景,研究科技创新领域的AI+数智化解决方案,推动科技创新与产业创新智能化发展。
高校如何快速构建科研能力画像,并通过智能化手段提升成果转化成功率?.docx
科易网基于40亿+科创知识图谱数据库,深度探索AI技术在技术转移、成果转化、技术经纪、知识产权、产业创新、科技招商等垂直领域的多样化应用场景,研究科技创新领域的AI+数智化解决方案,推动科技创新与产业创新智能化发展。
编写和运行简单脚本-下载即用.zip
打开链接下载源码: https://pan.quark.cn/s/f38ebab96530 在信息技术行业中,脚本语言被视为达成自动化操作的有效手段,对于初学者群体而言,这类语言具备较为平缓的学习门槛。本指南将详尽阐释编写及执行基础脚本的方法,旨在协助读者掌握此项技术。 我们需要明确脚本的基本定义。脚本通常是指由一连串指令构成的文本文档,这些指令将由解释器加以处理。诸如Python、JavaScript、Bash等脚本语言是我们常用的范例。在本案例中,我们或许会采用Bash脚本,因为它是Linux与Unix操作系统中普遍应用的命令行脚本语言。 标题所提及的“如何编写、运行简单的脚本”预示我们将学习构建一个基础脚本文件,并在适宜的环境中执行它。这一流程一般涵盖以下环节: 1. **构建脚本文件**:借助文本编辑工具(例如Notepad++、Visual Studio Code或Vim)创建一个新的文本文档,可将其命名为`script.sh`。务必在文档的开端加入一行`#!/bin/bash`,这被称为shebang,其作用是向系统指明应选用哪个解释器来执行该脚本。 2. **草拟脚本**:在文档内键入您的指令。譬如,您可以编写一个显示"Hello, World!"的脚本: ``` #!/bin/bash echo "Hello, World!" ``` 此处的`echo`命令是Bash中的一个内置指令,用于将后续内容展示在终端。 3. **存储并关闭文档**:确保正确地保存文档,并设定为文本格式。 4. **授予脚本执行许可**:在命令行界面,运用`chmod`指令赋予脚本执行权限。例如: ``` chmod +x script.sh ``` 5. **执行脚本**:...
云服务器部署jenkins:docker-compose.yml
云服务器部署jenkins:docker-compose.yml
高校科研院所如何构建智能化的知识图谱?.docx
科易网基于40亿+科创知识图谱数据库,深度探索AI技术在技术转移、成果转化、技术经纪、知识产权、产业创新、科技招商等垂直领域的多样化应用场景,研究科技创新领域的AI+数智化解决方案,推动科技创新与产业创新智能化发展。
最新推荐

![Python Data Structures and Algorithms [2017]](https://img-home.csdnimg.cn/images/20210720083646.png)



