Papers by Author: Lei Shi

Abstract: A model for the isothermal flow-induced crystallization (FIC) of polypropylene melt in a simple shear flow is developed. The model is based on the molecular kinetic theory. The first normal stress difference of the stress tensor, calculated according to a molecular model, is assumed as the driving force of the flow-induced nucleation. Crystallization is described as a spherulitical nucleation and growth process. The theoretical predictions of the evolution of the viscosity in steady shear flow of iPP are in agreement with the experimental findings. The relative influence of the mechanical and thermal phenomena on the crystallization development is then analyzed as a function of the shearing intensity in terms of nucleation density. The results show the enhancement of the crystallization kinetics due to the shearing.

Abstract: E-bussiness has grown rapidly in the last decade and massive amount of data on customer purchases, browsing pattern and preferences has been generated. Classification of electronic data plays a pivotal role to mine the valuable information and thus has become one of the most important applications of E-bussiness. Support Vector Machines are popular and powerful machine learning techniques, and they offer state-of-the-art performance. Rough set theory is a formal mathematical tool to deal with incomplete or imprecise information and one of its important applications is feature selection. In this paper, rough set theory and support vector machines are combined to construct a classification model to classify the data of E-bussiness effectively.