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An Imperfect Grouping Maintenance Strategy for Multi-Component Systems Using the Survival Signature 基于生存签名的多部件系统不完善分组维护策略
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-500-18
Jiaojiao Guo, H. Feng, Zhen Wang
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引用次数: 0
A Prediction Framework for Turning Period Structures in COVID-19 Epidemic and Its Application to Practical Emergency Risk Management 新冠肺炎疫情转折期结构预测框架及其在实际应急风险管理中的应用
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-309-29
Lan Di, Y. Gu, G. Qian, George Xianzhi YUAN
The aim of this paper is first to establish a general prediction framework for turning (period) term structures in COVID-19 epidemic related to the implementation of emergency risk management in the practice, which allows us to conduct the reliable estimation for the peak period based on the new concept of “Turning Period” (instead of the traditional one with the focus on “Turning Point”) for infectious disease spreading such as the COVID-19 epidemic appeared early in year 2020. By a fact that emergency risk management is necessarily to implement emergency plans quickly, the identification of the Turning Period is a key element to emergency planning as it needs to provide a time line for effective actions and solutions to combat a pandemic by reducing as much unexpected risk as soon as possible. As applications, the paper also discusses how this “Turning Term (Period) Structure” is used to predict the peak phase for COVID-19 epidemic in Wuhan from January/2020 to early March/2020. Our study shows that the predication framework established in this paper is capable to provide the trajectory of COVID-19 cases dynamics for a few weeks starting from Feb.10/2020 to early March/2020, from which we successfully predicted that the turning period of COVID-19 epidemic in Wuhan would arrive within one week after Feb.14/2020, as verified by the true observation in the practice. The method established in this paper for the prediction of “Turning Term (Period) Structures” by applying COVID-19 epidemic in China happened early 2020 seems timely and accurate, providing adequate time for the government, hospitals, essential industry sectors and services to meet peak demands and to prepare aftermath planning, and associated criteria for the Turning Term Structure of COVID-19 epidemic is expected to be a useful and powerful tool to implement the so-called “dynamic zero-COVID-19 policy” ongoing basis in the practice. © 2022, Science Press (China). All rights reserved.
本文的目的是首先在实践中建立与实施应急风险管理相关的COVID-19疫情转折(期)期限结构的通用预测框架,使我们能够基于新的“转折期”概念(而不是传统的以“转折点”为重点的概念)对2020年初出现的COVID-19疫情等传染病传播的高峰时段进行可靠的估计。由于应急风险管理是迅速实施应急计划的必要条件,因此确定转折期是应急规划的一个关键要素,因为它需要为有效行动和解决办法提供一个时间表,以便尽快减少尽可能多的意外风险,从而抗击大流行病。作为应用,本文还讨论了如何利用该“转折期(期)结构”预测2020年1月至2020年3月初武汉新冠肺炎疫情的高峰阶段。我们的研究表明,本文建立的预测框架能够提供2020年2月10日至2020年3月初几周内的COVID-19病例动态轨迹,由此我们成功预测了2020年2月14日之后一周内武汉COVID-19疫情的转折期,并得到了实践中真实观察的验证。本文建立的以2020年初中国发生的新冠肺炎疫情为例预测“转折期(期)结构”的方法及时准确,为政府、医院、关键行业和服务部门满足高峰需求和做好善后规划提供了充足的时间。以及相关的新冠肺炎疫情周转期限结构标准,有望在实践中成为实施所谓“动态零疫情政策”的有效有力工具。©2022,中国科学出版社。版权所有。
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引用次数: 0
Basic Research, Technological Innovation, and Firm Performance: The Empirical Analysis from Huawei Data 基础研究、技术创新与企业绩效:来自华为数据的实证分析
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-084-19
Xiangyu Zhu, Zhizhen Guo, Yang Yang
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引用次数: 0
DIUN: Deeper Inception U-Network for Recovering Partial Pixelated Images DIUN:用于恢复部分像素化图像的更深初始u网络
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-193-10
Hufei Yu, Shiwen He, Min Zhang, Wenwu Xie, Yan Tang
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引用次数: 0
Graph Attention Networks for Multiple Pairs of Entities and Aspects Sentiment Analysis in Long Texts 面向长文多对实体和方面情感分析的注意网络图
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-203-13
Jie Leng, Xijin J. Tang
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引用次数: 0
Analysis on the Output Elasticity and Contribution Rate of Energy Consumption to Economic Growth in China’s Yangtze River Economic Zone 中国长江经济带能源消费产出弹性与经济增长贡献率分析
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-150-17
M. Cheng, Yun Liu, Jianuo Li, Bin Liu
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引用次数: 0
Disclosure of Critical Audit Matters, Audit Risk and Audit Opinion 审计关键事项的披露、审计风险与审计意见
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-354-34
Xiaojuan Yang, Shixiang Dai
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引用次数: 0
Impacts of China’s Emergence on the World Economy: A Value Chain Perspective 中国崛起对世界经济的影响:价值链视角
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-575-23
G. Xing, Aolin Leng, Zongxian Feng, Yuan Zhang
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引用次数: 0
Prediction of Shanghai Stock Index Based on Investor Sentiment and CNN-LSTM Model 基于投资者情绪和CNN-LSTM模型的上证指数预测
Pub Date : 2022-01-01 DOI: 10.21078/jssi-2022-620-13
Yi Sun, Qingsong Sun, Shanwen Zhu
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引用次数: 1
Blockchain Technology: Theory and Applications Special Issue 区块链技术:理论与应用特刊
Pub Date : 2021-01-01 DOI: 10.21078/jssi-2021-issue3-0
D. Du, J. Li, Yongwu Li
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引用次数: 0
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