[Kubernetes] How to install Kubernetes Dashboard and without invalid certification

When I follow the instructions from the official site: https://github.com/kubernetes/dashboard to install Kubernetes Dashboard, I encounter the problem that I cannot access the dashboard via my browser because the certificate is invalid. After figuring it out, Here is my approach to resolving it.

[DDS] Install OpenSplice DCPS Python API on Raspberry Pi 3

Before starting to introduce how to install OpenSplice DCPS Python API on Raspberry Pi 3, we can take a look at the guide of OpenSplice DCPS Python API as list:

http://download.prismtech.com/docs/Vortex/html/ospl/PythonDCPSAPIGuide/index.html

[Kubernetes] The example of commands for commonly checking kubernetes status and troubleshooting

This post is about the example of commands for checking kubernetes status and troubleshooting. The purpose is for the reference by myself.

[Python] The issues of converting Python2 to Python3

If you are working on converting Python2 source code to Python3, there are some issues you will encounter sooner or later. I arrange my part here and will continue to update it as follows:

[Qt] The Qt features of WebAssembly and Qt quick WebGLStreaming

I recently noticed that there are 2 major Qt features: Qt WebAssembly and Qt quick WebGL which are very powerful and useful. For the Qt WebAccembly, any your C++ Qt applications could be executed on a browser. For Qt quick WebGL, it is optimized for Qt Quick and allows you to run remote Qt Quick applications in a browser.

Qt WebAssembly

Qt for WebAssembly

https://doc.qt.io/qt-5/wasm.html

Get started with Qt for WebAssembly

https://blog.qt.io/blog/2018/11/19/getting-started-qt-webassembly/

Qt WebAssembly 內容介紹
https://qtdream.com/topic/1081/qt-webassembly-%E5%86%85%E5%AE%B9%E4%BB%8B%E7%BB%8D/2

Here is a presentation about Qt for WebAccembly.

QtWS18 – Qt for WebAssembly by Morten Sørvig, The Qt Company

Qt WebAssembly Examples
https://github.com/msorvig/qt-webassembly-examples

Qt For WebAssembly Examples
(source code: https://github.com/msorvig/qt-webassembly-examples)
SensorTagDemo
colordebugger
gui_lifecycle
gui_localfiles
gui_opengl
gui_raster
mqtt_simpleclient
quick_clocks
quick_controls2_gallery
quick_controls2_testbench
quick_hellosquare
slate
widget_wiggly
widgets_wiggly

https://www.jianshu.com/p/bed6c2963435

Qt quick WebGL 

Here is a quick introduction to Qt quick WebGL

https://blog.qt.io/blog/2018/11/23/qt-quick-webgl-release-512/

The introduction of Qt Quick WebGL Streaming

https://blog.qt.io/blog/2017/02/22/qt-quick-webgl-streaming/

WebGL streaming in a Raspberry PI Zero W

https://blog.qt.io/blog/2017/03/24/webgl-streaming-raspberry-pi-zero-w/

Related Demo:

https://github.com/AVGP/streaming-webgl-demo

[Shared Library] How to check the used shared libraries in your program

This post is only to show the command about checking the used shared libraries in your program.

[DDS] Install OpenSplice Community Version

What is DDS? The Data Distribution Service (DDS™) is a middleware protocol and API standard for data-centric connectivity from the Object Management Group® (OMG®). It integrates the components of a system together, providing low-latency data connectivity, extreme reliability, and a scalable architecture that business and mission-critical Internet of Things (IoT) applications need. For more information, check it out: https://www.dds-foundation.org/what-is-dds-3/
https://zhuanlan.zhihu.com/p/32278571

In this post, I install OpenSplice as my DDS runtime environment and library. You can download it from here: https://www.adlinktech.com/en/dds-community-software-evaluation.aspx

[TensorFlow] Build TensorFlow from source with Intel MKL enabled

Based on this document "Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation",  I give a quick summary to do it.
Here are the steps for building TensorFlow from source with Intel MKL enabled.

For MKL DNN:

# Install Intel MKL & MKL-DNN
$ git clone https://github.com/01org/mkl-dnn.git
$ cd mkl-dnn
$ cd scripts && ./prepare_mkl.sh && cd ..
$ mkdir -p build && cd build && cmake .. && make -j$(nproc)
$ make test
$ sudo make install

For building TensorFlow: