A node.js server that receives IoT sensor data and broadcast it via web Introduction I constantly strive to easily access real-time, high-frequency data streams, or remotely deploy sensor data. Following data acquisition, the convenience of analyzing or visualizing this sensor data through algorithms is essential. This is a basic project that allows the Sensor_driven_by_MCU submit the data on to the nodejs_driven_server and allows the user record the data via web page that receives data from the nodejs_driven_server via WebSocket. see the diagram below:

B站分集视频时长获取与统计方法 学习B站分集视频时，若需要知道视频总时长，可用js把标题及时长在控制台输出，然后复制存为文本文件。 【使用方法】： 按下F12（Opt+CMD+I）进入开发者工具， 点击“Console”标题进入控制台， 在光标闪动的输入处粘贴以下代码并回车： var box=document.getElementsByClassName('list-box')[0]; var boxtext=box.innerText; var textline=boxtext.replace(/\n(?!P\d+)/g,' '); console.log(textline); 打开ChatGPT, 提问： 我要给你一个列表，你需要识别每个条目的时长。把它们的总时长加起来。你不用打印每个条目的时长。我只需要你打印出加和后的总时长即可。 条目如下： P1 001-入门到实战导学视频1 11:10 P2 002-第一天课程介绍1 05:54 P3 003-第一天课程介绍2 15:54

Linux内核升级与开启TCP BBR Reference: https://github.com/iMeiji BBR 目的是要尽量跑满带宽，并且尽量不要有排队的情况，效果并不比速锐差。 Linux kernel 4.9+ 才支持 tcp_bbr。下面简单讲述基于 KVM 架构的 virtual p server 如何开启。 附： OpenVZ 架构VPS开启BBR（容易导致判定滥用ban机，慎用！） Debian/Ubuntu TCP BBR 魔改版（不支持4.13.*及更新的内核） Debian 8+ / Ubuntu 14.04 下载最新内核，最新内核查看这里 http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.16/linux-image-4.16.0-041600-generic_4.16.0-041600.201804012230_amd64.deb 安装内核 dpkg -i linux-image-4.*.deb 删除旧内核（可选） dpkg -l | grep linux-image apt-get purge <旧内核> 更新 grub 系统引导文件并重启 update-grub reboot Ubuntu 16.04 安装 Hardware Enablement Stack (HWE)，自动更新内核 apt install --install-recommends linux-generic-hwe-16.04 删除旧内核（可选） sudo apt autoremove CentOS 6 下载更换内核，最新内核查看这里 rpm --import https://www.elrepo.org/RPM-GPG-KEY-elrepo.org rpm -Uvh http://www.elrepo.org/elrepo-release-6-8.el6.elrepo.noarch.rpm yum --enablerepo=elrepo-kernel install kernel-ml -y 查看内核是否安装成功 rpm -qa | grep kernel 删除旧内核（可选） rpm -ev <旧内核> 更新 grub 系统引导文件并重启 sed -i 's:default=.

Fixing VirtualBox Guest Additions: Kernel headers not found for target kernel OS system for testing: CentOS7 1. why this error: The version of kernel-devel does not match the version of your running kernel. You can check them by running uname -r and rpm -q kernel-devel. 2. update the kernel follow the link or do the following: # yum update -y # rpm --import https://www.elrepo.org/RPM-GPG-KEY-elrepo.org # yum install https://www.elrepo.org/elrepo-release-7.el7.elrepo.noarch.rpm # yum --disablerepo="*" --enablerepo="elrepo-kernel" list available # yum --enablerepo=elrepo-kernel install kernel-ml-devel kernel-ml -y #or: # yum –-enablerepo=elrepo-kernel install kernel-lt-devel kernel-lt -y # reboot After update the kernel, you can find the not-the-newest version of kernel.

Across folders’ module calling in python This topic involves understainding: how Py modules system works organizing your proj. files’ structure using the appropriate import systements 1. Proj. Structure 1.1 Packages and Modules ❤️A module is a Python file containing code and definitions. A module is just a Python program that ends with .py extension ❤️A package is a directory that contains a special __init__.py file, making it a Python package. A folder that contains a module becomes a package. see:

The URL tricks to save YouTube offline The ways below show you the most direct method to download YouTube videos by changing URL without any software. Try any of them as you need. Method 1: Change YouTube to ssyoutube youtube.com/watch?v=C6MVEwl0ceI&t=2s -> ssyoutube.com/watch?v=C6MVEwl0ceI&t=2s Method 2: Change YouTube to youpak youtube.com/watch?v=C6MVEwl0ceI&t=2s -> youpak.com/watch?v=C6MVEwl0ceI&t=2s Method 3: Change YouTube to youtubepp youtube.com/watch?v=C6MVEwl0ceI&t=2s -> youtubepp.com/watch?v=C6MVEwl0ceI&t=2s Method 4: Change YouTube to pwnyoutubepp youtube.com/watch?v=C6MVEwl0ceI&t=2s -> pwnyoutube.com/watch?v=C6MVEwl0ceI&t=2s FAQ: Are there any video quality restrictions when downloading from YouTube

3 Ways to Convert Python App into APK When you write an android app with python (see how to), with packages like kivy, it is suffering that convert your Python code into installable/runable APK file for real mobile Android devices. This blog is borrowing Kaustubh Gupta’s blog and is re-edited to introduce the 3 ways to obtain the APK from Python Android app code. 1. The challege we need to package the python code properly, otherwise, Python apps build with Kivy cannot be directly transferred to android devices.

Example of Nginx Reverse Proxy Configuration server { listen 80; listen [::]:80; server_name <your_server_name>; rewrite ^(.*)$ https://$host$1 permanent; } map $http_upgrade $connection_upgrade { default upgrade; '' close; } server { listen 443 ssl http2; listen [::]:443 ssl http2; server_name <your_server_name>; ssl_certificate /path/to/ssl_cert; ssl_certificate_key /path/to/ssl_cert_key; location / { proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header X-Forwarded-Proto $scheme; proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection $connection_upgrade; proxy_pass http://127.0.0.1:9000/; } } Example of Caddy Reverse Proxy Configuration # This is a comment yourdomain.

Custom IPython Jupyter Notebook keyboard shortcut to duplicate current line in edit mode For Microsoft Windows User (pcDefault) Create a new JS file under ~/.jupyter/custom/custom.js if it does not exist, and add the next code: /** * * Duplicate a current line in the Jupyter Notebook * Used only CodeMirror API - https://codemirror.net * **/ CodeMirror.keyMap.pcDefault["Ctrl-Down"] = function(cm){ // get a position of a current cursor in a current cell var current_cursor = cm.doc.getCursor(); // read a content from a line where is the current cursor var line_content = cm.

1. Load data and get to know the meta data import pydicom raw_medical_image = pydicom.read_file(file_path) print(raw_medical_image) medical_image = raw_medical_image.pixel_array plt.imshow(medical_image, cmap='gray') # cmap -- color map 2. Five steps of processing 2.1 Transforming to HU: obtain the HU by using Rescale_Intercept and Rescale_Slope headers: hu_image = image * medical_image.RescaleSlope + medical_image.RescaleIntercept #window_image: img_min = window_center - window_width // 2 img_max = window_center + window_width // 2 window_image = image.copy() window_image[window_image < img_min] = img_min window_image[window_image > img_max] = img_max 2.2 Removing Noises segmentation = morphology.