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How to determine the poor students is the premise and foundation of the poor students' aid work in the major colleges and universities. Although after many years of exploration and improvement, colleges and universities throughout the country have also formed a set of their own identification methods for poor students, but the implementation effect is not ideal. The identification of poor students is still a difficult problem for poor students in colleges and universities. This paper holds that in the process of determining the poor students, especially the index of relative poverty should be a series of index system which synthesizes many factors, but the data performance of these factors is fuzzy, so we can combine big data, Using Fuzzy Cluster Analysis to establish a complete method to determine Poverty The model can be used to accurately identify the poor students.

Abstract. In order to promote the practicality of smart phone identification based on gesture, we introduce weighted morphological characteristics and early termination of authentication into dynamic time warping (DTW) algorithm, which based on characteristic moving data captured by in-built accelerometer and gyroscopes, and put forward an effective identification algorithm (ME-DTW) for smartphone. The algorithm controls the contribution made by the difference between the latitudes to the total Euclidean distance by smartphone morphological characteristics. It also introduces restricted areas touch trigger gesture acquisition scheme and authentication gesture length selection scheme based on normal distribution, which effectively improve the identification accuracy and efficiency. Experimental results show that: when others imitate gestures attack false acceptance rate tends to 0%, the personal identification false rejection rate remained at 3.29%, which can meet most practical security needs