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Jian Li

Researcher at Xi'an Jiaotong University

Publications -  32
Citations -  415

Jian Li is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Categorical variable & Control chart. The author has an hindex of 9, co-authored 30 publications receiving 303 citations. Previous affiliations of Jian Li include Shaanxi Normal University & Tsinghua University.

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Production and transportation outsourcing decisions in the supply chain under single and multiple carbon policies

TL;DR: In this article, the authors examined the production and transportation outsourcing problems of a two-echelon supply chain under the cap-and-trade policy and joint cap and trade and carbon tax policy, and showed that the extended model with carbon policies is more beneficial for emissions reduction, and the effect of emissions reduction gradually becomes smooth as the carbon price increases.
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A Wavelet-Based Statistical Approach for Monitoring and Diagnosis of Compound Faults With Application to Rolling Bearings

TL;DR: Simulation results show the proposed approach outperforms existing methods, especially at an early stage, and will aim at improving the method’s sensitivity in distinguishing faults similar to each other.
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Multivariate binomial/multinomial control chart

TL;DR: In this article, a phase II control chart is proposed that is robust in efficiently detecting various shifts, especially those in interaction effects representing the dependence among factors, and the use of log-linear models for characterizing the relationship among categorical factors that are adapted into a framework of multivariate binomial and multivariate multinomial distributions.
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Directional Control Schemes for Multivariate Categorical Processes

TL;DR: A Phase II log-linear directional control chart is proposed that exploits directional shift information and integrates the monitoring of multivariate categorical processes into the unified framework ofMultivariate binomial and multivariate multinomial distributions.
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A simple categorical chart for detecting location shifts with ordinal information

TL;DR: In this paper, a simple ordinal categorical chart is proposed to detect location shifts in the latent variable based on merely the attribute level counts, regardless of the continuous values of a latent variable.