scholarly journals Research on early warning and control of public opinion based on Digital twin

2021 ◽  
Author(s):  
Wang Kai ◽  
Gao Yang ◽  
He Jie
Keyword(s):  
Public Opinion ◽  
Early Warning ◽  
Digital Twin ◽  
And Control

Communication

2017 ◽  
Author(s):  
Christian D. Liddy
Keyword(s):  
Public Opinion ◽  
Political Power ◽  
Political Process ◽  
The Political ◽  
Late Medieval ◽  
And Control ◽  
Ordinary Citizens

The exercise of political power in late medieval English towns was predicated upon the representation, management, and control of public opinion. This chapter explains why public opinion mattered so much to town rulers; how they worked to shape opinion through communication; and the results. Official communication was instrumental in the politicization of urban citizens. The practices of official secrecy and public proclamation were not inherently contradictory, but conflict flowed from the political process. The secrecy surrounding the practices of civic government provoked ordinary citizens to demand more accountability from town rulers, while citizens, who were accustomed to hear news and information circulated by civic magistrates, were able to use what they knew to challenge authority.

Deep Structured Learning for Natural Language Processing

2021 ◽  
Vol 20 (3) ◽  
pp. 1-14
Author(s):  
Yong Li ◽  
Xiaojun Yang ◽  
Min Zuo ◽  
Qingyu Jin ◽  
Haisheng Li ◽  
...  
Keyword(s):  
Public Opinion ◽  
Food Safety ◽  
Language Processing ◽  
Early Warning ◽  
Conditional Random Field ◽  
Semantic Features ◽  
Related Sequence ◽  
The Public ◽  
Network Public Opinion

The real-time and dissemination characteristics of network information make net-mediated public opinion become more and more important food safety early warning resources, but the data of petabyte (PB) scale growth also bring great difficulties to the research and judgment of network public opinion, especially how to extract the event role of network public opinion from these data and analyze the sentiment tendency of public opinion comment. First, this article takes the public opinion of food safety network as the research point, and a BLSTM-CRF model for automatically marking the role of event is proposed by combining BLSTM and conditional random field organically. Second, the Attention mechanism based on vocabulary in the field of food safety is introduced, the distance-related sequence semantic features are extracted by BLSTM, and the emotional classification of sequence semantic features is realized by using CNN. A kind of Att-BLSTM-CNN model for the analysis of public opinion and emotional tendency in the field of food safety is proposed. Finally, based on the time series, this article combines the role extraction of food safety events and the analysis of emotional tendency and constructs a net-mediated public opinion early warning model in the field of food safety according to the heat of the event and the emotional intensity of the public to food safety public opinion events.

G-GERT network model of online public opinion reversal based on kernel and grey degree

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shuli Yan ◽  
Xiangyan Zeng ◽  
Pingping Xiong ◽  
Na Zhang
Keyword(s):  
Public Opinion ◽  
Network Model ◽  
Design Methodology ◽  
Average Frequency ◽  
Decision Makers ◽  
Content Type ◽  
Gert Network ◽  
Frequency Probability ◽  
And Control ◽  
Difficult Issue

PurposeIn recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.Design/methodology/approachCombined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.FindingsThroughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.Originality/valueThe G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.

Boosting the Capabilities of Gas Stand Data Acquisition and Control Systems by Using a Digital Twin Based on a Holistic Turbocharger Model

2021 ◽  
Author(s):  
José R. Serrano ◽  
Luis Miguel García-Cuevas ◽  
Vishnu Samala ◽  
Juan Antonio López-Carrillo ◽  
Holger Mai
Keyword(s):  
Data Acquisition ◽  
Control Systems ◽  
Heat Fluxes ◽  
Testing Time ◽  
Time Saving ◽  
Digital Twin ◽  
Dimensional Modeling ◽  
On Line ◽  
And Control

Abstract During the last decade, increasingly advanced turbocharger models have been developed for sizing, engine matching and one-dimensional modeling. This work goes further and, instead of using these models for turbocharged engines design or analysis, it implements them in the data acquisition and control system of a turbocharger gas stand. This way, interesting new capabilities arise. The paper shows that there are important synergies between advanced turbocharger gas stand data acquisition and control systems and the modern turbocharger holistic models that have not been deeply exploited until now. They can be summarized as: on-line heat fluxes analysis, in-situ outlier testing points detection, testing time saving and using digital-twin techniques to monitor turbocharger health during testing.

scholarly journals Exploration on Prediction and Early Warning Technology for Investment Completion of 10 kV And Below Power Grid Infrastructure Projects

2020 ◽  
Vol 185 ◽  
pp. 01008
Author(s):  
Lei Ma ◽  
Fan Wen ◽  
Jian Huang ◽  
Xia Pan ◽  
Feifei Xu ◽  
...  
Keyword(s):  
Early Warning ◽  
Distribution Network ◽  
Management Mode ◽  
Infrastructure Projects ◽  
Investment Management ◽  
Plan Implementation ◽  
Support Tool ◽  
Investment Plan ◽  
Network Investment ◽  
And Control

The external severe and complex economic situation has a great impact on the efficiency of the company’s investment implementation. The in-depth implementation of the lean investment management concept also puts forward new requirements for improving the extensive distribution network investment management mode. In addition, in recent years, the proportion of investment in distribution network projects of 10kV and below has increased, and its management mode is difficult to keep up with the new investment management requirements. Therefore, this project takes the infrastructure projects of 10kV and below as the research object, constructs the investment plan curve by studying the business rules of construction, accounting and materials, and deepens its application in the early warning of investment plan implementation based on the investment plan line, and provides an effective support tool for the investment lean management and control of distribution network.

scholarly journals Escalation through Entanglement: How the Vulnerability of Command-and-Control Systems Raises the Risks of an Inadvertent Nuclear War

2018 ◽  
Vol 43 (1) ◽  
pp. 56-99 ◽  
Author(s):  
James M. Acton
Keyword(s):  
United States ◽  
Early Warning ◽  
The United States ◽  
Dual Use ◽  
Nuclear War ◽  
Organizational Reform ◽  
Starting Point ◽  
Cyber Espionage ◽  
Damage Limitation ◽  
And Control

Nonnuclear weapons are increasingly able to threaten dual-use command, control, communication, and intelligence assets that are spaced based or distant from probable theaters of conflict. This form of “entanglement” between nuclear and nonnuclear capabilities creates the potential for Chinese or Russian nonnuclear strikes against the United States or U.S. strikes against either China or Russia to spark inadvertent nuclear escalation. Escalation pressures could be generated through crisis instability or through one of two newly identified mechanisms: “misinterpreted warning” or the “damage-limitation window.” The vulnerability of dual-use U.S. early-warning assets provides a concrete demonstration of the risks. These risks would be serious for two reasons. First, in a conventional conflict against the United States, China or Russia would have strong incentives to launch kinetic strikes on U.S. early-warning assets. Second, even limited strikes could undermine the United States' ability to monitor nuclear attacks by the adversary. Moreover, cyber interference with dual-use early-warning assets would create the additional danger of the target's misinterpreting cyber espionage as a destructive attack. Today, the only feasible starting point for efforts to reduce the escalation risks created by entanglement would be unilateral measures—in particular, organizational reform to ensure that those risks received adequate consideration in war planning, acquisition decisions, and crisis decisionmaking. Over the longer term, unilateral measures might pave the way for more challenging cooperative measures, such as agreed restrictions on threatening behavior.

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