How to predict the students’ learning trend, according to the current situation of students' learning, is meaningful for the management of students' learning process. This paper presents a study early-warning system based on machine learning, using the method of machine learning with the data related to the scores of students’ professional courses, retaking percentage, graduation rate and bachelor's degree data of three classes of School of Information Engineering of Wuhan Business University, which establish a prediction model of student learning trend evaluation (whether there is a risk of not obtaining the degree). It provides reference for college students' study management and can improve the quality and efficiency of teaching management.

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This paper designs an intelligent blind people guide cane based on the analysis of basic functions of conventional guide canes. The hardware components of the cane design includes environmental monitoring modules, acoustic distance measurement module, vibration alert module and GPS positioning module etc. The system can provide real-time alerting of obstacles ahead and route selection through analyzing road conditions by means of GPS positioning module. The cane’s hardware system is designed with monitoring and analysis software to enhance the user’s using experience, while ensuring the functions of user security.

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