Smart hybrid isolation of a case study highway bridge exploiting seismic early warning information

2017 ◽  
Vol 147 ◽  
pp. 134-147 ◽  
Author(s):  
Iolanda Nuzzo ◽  
Nicola Caterino ◽  
Giuseppe Maddaloni ◽  
Antonio Occhiuzzi
Keyword(s):  
Early Warning ◽  
Highway Bridge ◽  
Seismic Early Warning ◽  
Hybrid Isolation

Fostering relations with a host country: A case study of the OSCE and Tadjikistan

2009 ◽  
Vol 20 (4) ◽  
pp. 339-345 ◽  
Author(s):  
Kathleen Samuel
Keyword(s):  
Conflict Management ◽  
Host Country ◽  
Early Warning ◽  
Daily Basis ◽  
Conflict Prevention ◽  
Post Conflict

AbstractThe OSCE's mandate for early warning, conflict prevention, conflict management and post-conflict rehabilitation based on its approach to comprehensive security through its network of field offices is implemented on a daily basis. Constructive relations with a host country are an important factor in their success, yet not always easy to achieve. This article provides a case study of one endeavour to strengthen these relations.

scholarly journals The Self-organizing Seismic Early Warning Information Network (SOSEWIN)

2009 ◽  
Vol 80 (5) ◽  
pp. 755-771 ◽  
Author(s):  
K. Fleming ◽  
M. Picozzi ◽  
C. Milkereit ◽  
F. Kuhnlenz ◽  
B. Lichtblau ◽  
...  
Keyword(s):  
Early Warning ◽  
The Self ◽  
Information Network ◽  
Seismic Early Warning ◽  
Self Organizing

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.

scholarly journals An Early Warning Model for School Dropout: a Case Study in E-learning Class

2019 ◽  
Author(s):  
Felipe Braz ◽  
Fernanda Campos ◽  
Victor Stroele ◽  
Mário Dantas
Keyword(s):  
Early Warning ◽  
School Dropout ◽  
Early Warning Model ◽  
E Learning ◽  
Warning Model
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