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Lingling Li

Researcher at Shanghai Jiao Tong University

Publications -  6
Citations -  83

Lingling Li is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & Supply chain. The author has an hindex of 1, co-authored 1 publications receiving 6 citations.

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Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments.

TL;DR: In this article, the evolutionary game model between the government and the household medical device enterprises is constructed to reduce the environmental pollution caused by abandoned household medical devices, based on the dynamic punishment and dynamic subsidy measures adopted by the government.
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Research on the Construction and Prediction of China's National Fitness Development Index System Under Social Reform

TL;DR: Wang et al. as discussed by the authors constructed an evaluation index system of the national fitness development index, including 4 first-level indicators, 14 second-level indicator, and 49 thirdlevel indicators.
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Dual-Source Procurement Strategy of Cross-Border E-Commerce Supply Chain considering Members’ Risk Attitude

TL;DR: In this article , a mean-variance model dominated by overseas retailers and reversely solves the risk-aversion attitude of a single cross-border supplier was proposed to analyze the impact of supply disruption probability, risk aversion coefficient, channel distribution coefficient, and other parameters on purchase price, market demand, target profit, and utility.
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Evaluation of Low-Carbon Scientific and Technological Innovation-Economy-Environment of High Energy-Consuming Industries

TL;DR: In this paper , the authors analyzed the coordinated development of scientific and technological innovation, economy, and environment of high energy-consuming industries from 2011 to 2019 and analyzed the factors restricting the coordination of the three systems.
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Research on Chest Disease Recognition Based on Deep Hierarchical Learning Algorithm

TL;DR: An efficient convolutional neural network with GCN, which is named SGGCN, is proposed to meet the need of efficient computation and considerable accuracy in diagnostic radiology and achieves a considerable performance.