Tonight, I attended the Wolfram 2020 08-20 China Student Ambassador Presentation via Zoom.
During the intermission, I won a grand prize of 3000RMB worth of System Modeler modeling program, which I am going to install on my MacBookPro to study various physical and biological modeling.
If you are interested in Mathematica, you can attend Wolfram 2020/09/08 China Virtual Technology Conference, where many big names will be speaking.
Mathematica Metaprogramming
When you mention MetaProgramming, you will think of Lisp, generating code by code is the strength of Lisp language, but Mathematica can also do a good job, from the presentation, learn how to generate a complex code by a simple and elegant code, a bit of art in it. I suddenly remembered the famous book SICP in computer science, and searched on Google to see if anyone had used Mathematica to learn SICP, and found that there were very few, so I decided to use Mathematica to implement the examples in SICP myself.
So I decided to use Mathematica to implement the example in SICP.
Mathematica Compilation
MMA can be speeded up with Compile, FunctionCompile, and we can also compile the MMA Code into C Code to get a complete binary file that is independent of the MMA runtime environment and can be run directly on the operating system.
One project worth learning from is MathCompile, which is much closer to functional programming than Compile.
Mathematica R-Link Processing Biomedical Information
Here we talk about how to do data analysis in Mathematica in conjunction with R. Most of the description describes how to use and code the data, but the examples in the medical field are not covered.
Mathematica Deep Retinal Analysis
I liked this presentation better because I have been working on deep learning in diseases lately, including deep detection of Covid-19, retinopathy, and prediction of cardiac and other diseases.
The presentation was basically about image collection, image pre-processing, image enhancement (to enhance image detail through DeepLearning), building a UNet image segmentation neural network (for segmenting retinal blood vessels and optic discs), training the neural network, and finally testing the accuracy of the network model, with the main goal of detecting and classifying retinopathy caused by diabetes, glaucoma, and macular degeneration.
A few screenshots of the PowerPoint.
Calling each other between Mathematica and Python
It’s basically two languages complementing each other, Python for a lot of low-level trivial stuff and Mathematica for high-level functions.
Write at the end
Expect 2020 Wolfram China Virtual Technology Conference
The sessions were as follows.
9/8 7 pm - 8 pm: Introduction to the Wolfram System Modeler--Shenghui Yang
9/8 8 pm - 9 pm: Wolfram Mathematica Overview - Dr. Rigorous
9/9 9 am - 10 am: Intelligent Question and Answer System Wolfram|Alpha Introduction -- Dr. Lu Meng
9/9 10 am - 11 am: Audio and Video Processing in Wolfram Language -- Chen Jianyu
9/9 6:30 pm - 7:15 pm: Designing Metal 3D Printed Industrial Grade Products with Mathematica -- Fei Wu
9/9 7:15 pm - 8:00 pm: Image Processing Techniques in the Wolfram Language -- Silvia Hao
9/9 8:00 pm - 9:00 pm: Applications of Wolfram Language to Planar Geometry -- Shenghui Yang
9/10 9 am - 10 am: Mathematica Graphical Imaging Language - Dr. Yuzhu Lu
9/10 10 am - 10:30 am: Wolfram Language Development Environment for Major Editors - Comintern
9/10 10:30 am - 11:30 am: Introduction to the Principles of Neural-like Networks and Their Use in Wolfram Language - Dr. Maochuang Ye
