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Articles by Tao Yang
Total Records ( 2 ) for Tao Yang
  Tao Yang and Yu Yang
  During the product design phase, due to various factors and random failures, input materials processed might be defective and would be less than input amount. In order to increase the output, defective products are usually formed as a reverse product flow and redesigned. However, these activities would cause an increment of the design capability and processing time for the design entities. The objective of this research is to propose a reliability evaluation model and solution method that would determine the reliability for the product design phase with reverse logistics product re-designing activities. The evaluation model contains design capability and processing time two aspects and the whole system reliability can be derived afterwards. Finally, a case study is presented to illustrate the usefulness of the proposed approach.
  Xintao Qiu , Dongmei Fu and Tao Yang
  Current data analysis methods in processing sensor data, does not take into account the different contribution between the new data and the old data for the whole dataset, which fails to reflect the importance of new data. In this paper, a recent-biased dimensionality reduction method is proposed for sensor data analysis, which uses a multilinear dimensionality reduction learning algorithm with forgetting factor introduced. With the proposed dimensionality reduction method, the impact of the new sample data for the future trend of sensor data is highlighted, which can avoid the dilemma of data saturation phenomenon; the sensor data is organized into high order tensor pattern, which keeps the original structure, discriminates information and integrity of the data. Moreover, in order to evaluate the proposed dimensionality reduction method, a new framework of datasets quality assessment is introduced. The experiment results show that, compared with principal component analysis and multilinear principal component analysis, the proposed novel dimensionality reduction method can be more effectively applied to analyzing the sensor data.
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