Construction of Corruption Early Warning Mechanism

2011 ◽  
Vol 204-210 ◽  
pp. 691-694
Author(s):  
Qiu Jun Guo ◽  
You De Zheng
Keyword(s):  
Early Warning ◽  
Index System ◽  
Early Warning Mechanism ◽  
The World ◽  
Information Basis ◽  
Operating Method

Anticorruption is becoming one of the most important problems in the world. Therefore, we established a mechanism to analyze the information of corruption and focused on the prior settled scenarios. We tried to construct a complete and efficient corruption early warning mechanism from four aspects, such as organization, information basis, operating method and index system. Based on the supervision, analysis and judgment, we use empirical social early warning methods to detect and forecast the corruption.

Study on Four-Color Early Warning Mechanism of Collapse Hazards in Subsea Tunnel

2012 ◽  
Vol 166-169 ◽  
pp. 2814-2820
Author(s):  
Yi Guo Xue ◽  
Shu Cai Li ◽  
Mao Xin Su ◽  
Dao Hong Qiu ◽  
Hao Tian
Keyword(s):  
High Risk ◽  
Early Warning ◽  
Preventive Measures ◽  
Tunnel Construction ◽  
Geological Hazards ◽  
Orange Yellow ◽  
Early Warning Mechanism ◽  
The World ◽  
Construction Risk ◽  
Subsea Tunnel

The long, and larger subsea tunnel has rapidly developemented in recent years in the world. But it has much more high risk for its geological condition's complexity and uncertainty in the physical prospecting interpretation result. The collapse is one of the biggest construction risk in the long, and larger subsea tunnel project, which can easily lead to huge disaster and economic and life loss. The four-color(red, orange, yellow and green) early warning mechanism of geological hazards on collapse in subsea tunnel construction is stated in the paper. And the corresponding project preventive measures are also made according to different early warning ranks. The early warning mechanism and methods stated above have some guiding significance to similar projects.

A Multi-parameter Joint Warning Mechanism for Physical Condition Monitoring System in Physical Education

2020 ◽  
Vol 14 (1) ◽  
pp. 113-119
Author(s):  
Zhang Su
Keyword(s):  
Physical Education ◽  
False Alarm ◽  
Real Time ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Early Warning ◽  
Physical Condition ◽  
School Students ◽  
Early Warning Mechanism ◽  
Number Of Segments

Background: In recent years, sudden deaths of primary and secondary school students caused by sports activities have drawn great attention in education and medical circles. It is necessary for schools to monitor the physical condition of the students in order to reasonably set the duration of their physical activity. At present, the physical condition monitoring instruments used in various hospitals are expensive, bulky, and difficult to operate, and the detection process is complicated. Therefore, existing approaches cannot meet the needs of physical education teachers on campus for detecting the physical condition of students. Methods: This study designs a portable human-physiological-state monitoring and analysis system. Real-time communication between a wearable measurement device and a monitoring device can be ensured by real-time detection of the environment and power control of the transmitted signal. Results: From a theoretical point of view, the larger the number of segments M, the more significantly the reduction of false alarm probability. The simulation results also show this fact. Compared with the conventional early warning mechanism, the probability of a false alarm for the proposed system is lower, and the greater the number of segments, the faster its reaction speed. Conclusion: The portable monitoring system of student physical condition for use in physical education of primary and middle school students proposed in this paper ensures real-time monitoring of the members within the system in an open environment, and further proposes an early warning mechanism for combining multiple vital sign parameters. In addition, the proposed system functions faster; the average early warning time required is only one-quarter of that of the conventional system.

Evaluation of emergency management capability of urban community based on entropy weight and multi-layer fuzzy

2021 ◽  
pp. 1-9
Author(s):  
Wang Yuansheng ◽  
Zhang Ying ◽  
Guo Xinyao
Keyword(s):  
Emergency Management ◽  
Index System ◽  
Comprehensive Evaluation ◽  
Urban Community ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Entropy Weight ◽  
Management Capability ◽  
The World ◽  
Comprehensive Evaluation Model

At present, various public emergencies occur frequently around the world, and the world has entered the stage of a “high-risk society”. Urban community as the carrier of all kinds of public emergencies, its role has become increasingly prominent and become the focus of the current research, but in the urban community emergency management capacity evaluation system, the related studies are still less. To more effectively identify the key internal and external factors that affect the emergency management ability of the urban community, and evaluate scientifically and effectively, on the basis of the existing studies, the evaluation index system of community emergency management capability was established according to the emergency management cycle theory. In view of the complexity and fuzziness of the emergency management capability of the urban community, a multi-layer fuzzy comprehensive evaluation model based on entropy weight was established, and the emergency management capability evaluation of community was carried out under the background of the public emergency event of COVID-19 epidemic. The results show that the evaluation results and improvement suggestions of the multi-layer fuzzy comprehensive evaluation model based on entropy weight are consistent with the actual situation, indicating that the index system and the selected method are reasonable and effective. This study provides a new decision-making idea and method for the evaluation of urban community emergency management capability, and has high application value.

Early Warning Mechanism for the Surge of Passengers in Metro Systems Based on Automated Fare Collection Data: Case Study of Guangzhou, China

2019 ◽  
Vol 2673 (4) ◽  
pp. 917-929 ◽  
Author(s):  
Ning Huan ◽  
Enjian Yao ◽  
Binbin Li
Keyword(s):  
Early Warning ◽  
Traffic Control ◽  
Safety Management ◽  
Early Stage ◽  
Point Of View ◽  
Control Measures ◽  
Passenger Flow ◽  
Early Warning Mechanism ◽  
Metro Systems

Recently, surges of passengers caused by large gatherings, temporary traffic control measures, or other abnormal events have frequently occurred in metro systems. From the standpoint of the operation managers, the available information about these outside events is incomplete or delayed. Unlike regular peaks of commuting, those unforeseen surges pose great challenges to emergency organization and safety management. This study aims to assist managers in monitoring passenger flow in an intelligent manner so as to react promptly. Compared with the high cost of deploying multisensors, the widely adopted automated fare collection (AFC) system provides an economical solution for inflow monitoring from the application point of view. In this paper, a comprehensive framework for the early warning mechanism is established, including four major phases: data acquisition, preprocessing, off-line modeling, and on-line detection. For each station, passengers’ tapping-on records are gathered in real time, to be further transformed into a dynamic time series of inflow volumes. Then, a sequence decomposition model is formulated to highlight the anomaly by removing its inherent disturbances. Furthermore, a novel hybrid anomaly detection method is developed to monitor the variation of passenger flow, in which the features of inflow patterns are fully considered. The proposed method is tested by a numerical experiment, along with a real-world case study of Guangzhou metro. The results show that, for most cases, the response time for detection is within 5 min, which makes the surge phenomenon observable at an early stage and reminds managers to make interventions appropriately.

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