During my undergraduated period, I did some projects required by college courses. I have gained much from those projects. I broadened the horizon of Computer Science subject and strengthened my ability of programming.
This project requires a system that a car based on a microcontroller can find the road automatically with the assistant of a computer. In this project, we use the black thick line to serve as the road that the car should follow. A camera connected to computer can take the immediate video of the car running on the black line and send instructions to navigate the car automatically.
This is a pipelined CPU based on MIPS instruction set that runs on the Xilinx FPGA Spartan 3E developing board. It is designed by Verilog and Xilinx ISE Designed Suit. If you have the Xilinx FPGA Spartan 3E development board, you can download the code on your board and try to test it. If you don't have suitable developing board, it's ok to simulate its performance by the Xilinx ISE Designed Suit.
This project requires a system that a car based on a microcontroller can run and transfer video under the control of a smartphone. It has some relation to the pervious project of EE Lab IIB. However, this time the car should receive the instructions from the smartphone by bluetooth. You can use buttons in the unique smartphone application to control it. Apart from the button, you can even use gravity sensor or voice recognition functions to control the car.
This software is a text editor with fingerprint recognition system. It's based on Java and need to be used with a fingerprint collector. To bring the security conception into consideration, we add the fingerprint recognition system into a rich text editor. Users can bind their fingerprints to an encrypted text files that it need correct fingerprints to open the files. Besides, the file itself is encrypted by DES and it's difficult to be cracked by outside programs.
This is a simple compiler of Tiger Language in the work of Modern Compiler Implementation in Java. It's an unfinished version, It has implemented the Lexical Analysis, Parsing, Semantic Analysis, Active Record, and Intermediate Code Generation.
The project trained some classifiers to classify the gene chip data into several kinds by machine learning methods and deep learning methods respectively, including Logistic Regression(LR), Support Vector Machine(SVM), and Deep Belief Network(DBN). A project report is attached. Original data is available at here with the code 5q32.
This is a simple spider program that can get informations from dianping.com based on users. You can get personal information and all review information of a certain user. The spider program uses random agent list and proxies to prevent itself from being detected by anti-robot program(if exists).
This is a Pytorch implementation of BiGCN model in paper: Predicting Emergency Medical Service Demand with Bipartite Graph Convolutional Networks
This is a Pytorch implementation of the model in paper: Predicting Potential Real-time Donations in YouTube Live Streaming Services via Continuous-time Dynamic Graph