scholarly journals The Level of Public Acceptance to the Development of a Coastal Flooding Early Warning System in Jakarta

2021 ◽  
Vol 13 (2) ◽  
pp. 566
Author(s):  
Nelly Florida Riama ◽  
Riri Fitri Sari ◽  
Henita Rahmayanti ◽  
Widada Sulistya ◽  
Mohamad Husein Nurrahmat
Keyword(s):  
Path Analysis ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Coastal Flooding ◽  
Coastal Areas ◽  
Public Acceptance ◽  
Community Attitudes ◽  
Early Warning Model ◽  
Warning Model

Coastal flooding is a natural disaster that often occurs in coastal areas. Jakarta is an example of a location that is highly vulnerable to coastal flooding. Coastal flooding can result in economic and human life losses. Thus, there is a need for a coastal flooding early warning system in vulnerable locations to reduce the threat to the community and strengthen its resilience to coastal flooding disasters. This study aimed to measure the level of public acceptance toward the development of a coastal flooding early warning system of people who live in a coastal region in Jakarta. This knowledge is essential to ensure that the early warning system can be implemented successfully. A survey was conducted by distributing questionnaires to people in the coastal areas of Jakarta. The questionnaire results were analyzed using cross-tabulation and path analysis based on the variables of knowledge, perceptions, and community attitudes towards the development of a coastal flooding early warning system. The survey result shows that the level of public acceptance is excellent, as proven by the average score of the respondents’ attitude by 4.15 in agreeing with the establishment of an early warning system to manage coastal flooding. Thus, path analysis shows that knowledge and perception have a weak relationship with community attitudes when responding to the coastal flooding early warning model. The results show that only 23% of the community’s responses toward the coastal flooding early warning model can be explained by the community’s knowledge and perceptions. This research is expected to be useful in implementing a coastal flooding early warning system by considering the level of public acceptance.

Development of early warning system for linear engineering - a case study on highway in Sichuan, China

2020 ◽  
Author(s):  
Ruihua Xiao
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Highway Safety ◽  
Warning Systems ◽  
Safety Control ◽  
Early Warning Model ◽  
Landslide Early Warning ◽  
Warning Model

<p>For the recent years, highway safety control under extreme natural hazards in China has been facing critical challenges because of the latest extreme climates. Highway is a typical linear project, and neither the traditional single landslide monitoring and early warning model entirely dependent on displacement data, nor the regional meteorological early warning model entirely dependent on rainfall intensity and duration are suitable for it. In order to develop an efficient early warning system for highway safety, the authors have developed an early warning method based on both monitoring data obtained by GNSS and Crack meter, and meteorological data obtained by Radar. This early-warning system is not each of the local landslide early warning systems (Lo-LEWSs) or the territorial landslide early warning systems (Te-LEWSs), but a new system combining both of them. In this system, the minimum warning element is defined as the slope unit which can connect a single slope to the regional ones. By mapping the regional meteorological warning results to each of the slope units, and extending the warning results of the single landslides to the similar slope units, we can realize the organic combination of the two warning methods. It is hopeful to improve the hazard prevention and safety control for highway facilities during critical natural hazards with the progress of this study.</p>

scholarly journals Sepsis prediction via the clinical data integration system in the ICU

2021 ◽  
Author(s):  
Qiyu Chen ◽  
Ranran Li ◽  
Zhizhe Lin ◽  
Zhiming Lai ◽  
Peijiao Xue ◽  
...  
Keyword(s):  
Data Integration ◽  
Medical Devices ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Integration System ◽  
Integration Platform ◽  
Early Warning Model ◽  
Data Integration System ◽  
Warning Model

Sepsis is an essential issue in critical care medicine, and early detection and intervention are key for survival. We established the sepsis early warning system based on a data integration platform that can be implemented in ICU. The sepsis early warning module can detect the onset of sepsis 5 hours proceeding, and the data integration platform integrates, standardizes, and stores information from different medical devices, making the inference of the early warning module possible. Our best early warning model got an AUC of 0.9833 in the task of detect sepsis in 4 hours proceeding on the open-source database. Our data integration platform has already been operational in a hospital for months.

Early-Warning Model for Tourism Environment Carrying Capacity in Scenic Spots Based on Fuzzy Inference

2012 ◽  
Vol 605-607 ◽  
pp. 2405-2408
Author(s):  
Xiu Ping Yang ◽  
Er Chao Li
Keyword(s):  
Mathematical Model ◽  
Nonlinear System ◽  
Early Warning ◽  
Carrying Capacity ◽  
Early Warning System ◽  
Fuzzy Inference ◽  
Warning System ◽  
Inference System ◽  
Early Warning Model ◽  
Warning Model

Early-warning system of tourism environment carrying capacity (TECC) in scenic spots is a highly complicated nonlinear system. It is very difficult to establish an accuracy mathematical model. Fuzzy inference system adapts to the nonlinear system that doesn’t get an accuracy mathematical model and has uncertain factor. It has strong robustness and adaptability. Index of early-warning system of TECC in scenic spots is established, extracts fuzzy rules based on historical data, and simulates the early-warning system based on fuzzy inference. At last, taking Nandaihe international amusement centre scenic spot as an example proves that the early-warning model designed is feasible and effective.

Early-Warning Research for Carrying Capacity in Scenic Spots and its Application

2013 ◽  
Vol 373-375 ◽  
pp. 2209-2213
Author(s):  
Xiu Ping Yang ◽  
Er Chao Li
Keyword(s):  
Early Warning ◽  
Carrying Capacity ◽  
Early Warning System ◽  
Warning System ◽  
Quantitative Model ◽  
Early Warning Model ◽  
Predict Model ◽  
Warning Model ◽  
Model Support

The paper deeply studies early-warning system of carrying capacity in scenic spots, providing quantitative model support for early-warning system of carrying capacity. Indexes of early-warning system of carrying capacity in scenic spots is established, use GM(1,1) model to construct warning degree predict model. At last, Jifa agricultural ecological sightseeing garden as an example proves that the early-warning model designed is feasible and effective.

Early-Warning Model for TECC Based on Gray Neural Network - Taking Laolongtou Scenic Area as an Example

2013 ◽  
Vol 397-400 ◽  
pp. 2435-2438
Author(s):  
Xiu Ping Yang ◽  
Er Chao Li
Keyword(s):  
Neural Network ◽  
Early Warning ◽  
Early Warning System ◽  
Historical Data ◽  
Fuzzy Inference ◽  
Warning System ◽  
Forecasting Model ◽  
Error Signal ◽  
Single Feature ◽  
Warning Model

Based on fuzzy inference and gray neural network, indexes of early-warning system of carrying capacity in scenic spots is established and extract fuzzy rules based on historical data, simulate the early-warning system based on fuzzy inference, gray forecasting model is built for single feature index respectively, add a compensated error based on neural network. The prediction value equals to the output value of grey neural network model plus the compensated error signal. At last, takes Laolongtou scenic area as an example.

Design and Application of Risk Early-Warning System of Electric Power Engineering Projects - A Case Study of Combined Heat and Power Project in Western China

2013 ◽  
Vol 278-280 ◽  
pp. 2113-2117
Author(s):  
Qing Miao ◽  
Zhen Tao Xia
Keyword(s):  
Electric Power ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Power Engineering ◽  
Western China ◽  
Electric Power Engineering ◽  
Warning Model ◽  
Fuzzy Comprehensive Appraisal ◽  
Engineering Projects

Based on the theories of fuzzy set and fuzzy conversion, the method of fuzzy comprehensive appraisal is a decision-making process which combines qualitative analysis and quantitative analysis and can be used to forecast risk of electric power engineering projects. Using the method of AHP to establish risk early-warning indicators system and method of fuzzy comprehensive appraisal to establish risk early-warning model, the paper constitutes risk early-warning system of electric power engineering projects. A case from western China is applied to prove the validity of the risk early-warning system.

Gap Assessment of Warning and Dissemination Process of Early Warning System in Coastal Areas of Sri Lanka

2019 ◽  
pp. 36-44
Author(s):  
H. M. S. S. Hippola ◽  
E. M. S. D. Jayasooriya ◽  
G. P. Jayasiri ◽  
Chameera Randil ◽  
Chamal Perera ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Coastal Areas ◽  
Dissemination Process

scholarly journals Development of an operational coastal flooding early warning system

2012 ◽  
Vol 12 (2) ◽  
pp. 379-390 ◽  
Author(s):  
D.-J. Doong ◽  
L. Z.-H. Chuang ◽  
L.-C. Wu ◽  
Y.-M. Fan ◽  
C. C. Kao ◽  
...  
Keyword(s):  
Storm Surge ◽  
Early Warning ◽  
System Integration ◽  
Early Warning System ◽  
Warning System ◽  
Wave Model ◽  
Warning Signal ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Astronomical Tide

Abstract. Coastal floods are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding. The purpose of this study is to develop a coastal flooding early warning system (CoFEWs) by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability of offering data for the past, information for the present and future. The system was developed for the Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data sources is the system kernel. Numerical ocean models play an important role within the system because they provide data for assessment of possible flooding. The regional wave model (SWAN) that nested with the large domain wave model (NWW III) is operationally set up for coastal wave forecasting, in addition to the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. An example of the system operation during the Typhoon Haitung which struck Taiwan in 2005 is illustrated in this study.

The Research on Long-Term Financial Early-Warning System of Listed Companies

2013 ◽  
Vol 670 ◽  
pp. 216-221 ◽  
Author(s):  
Wei Ming Mou ◽  
Shui Bin Gu
Keyword(s):  
Financial Crisis ◽  
Early Warning ◽  
Early Warning System ◽  
Stock Exchange ◽  
Warning System ◽  
Listed Companies ◽  
Special Treatment ◽  
Warning Model ◽  
First Time

The article takes listed companies as research samples. Firstly, it selects 36 ST or *ST companies listed in Shanghai and Shenzhen Stock Exchange Market, who received special treatment during 2007 to 2009 for the first time and it also chooses another 36 normal companies as paired ones. Then, after using Factor analysis for identifying indexes, the paper go on with utilizing logistic to structure a financial long-term warning model. To verify the effectiveness of the model, the paper selects another 12 financial crisis companies and 12 financial fit companies to test. The results come out to show that establishing an effective long-term financial early-warning system helps enterprises to avoid financial crisis.

scholarly journals Developing an early warning system for storm surge inundation in the Philippines

2014 ◽  
Vol 2 (10) ◽  
pp. 6241-6270
Author(s):  
J. Tablazon ◽  
C. V. Caro ◽  
A. M. F. Lagmay ◽  
J. B. L. Briones ◽  
L. Dasallas ◽  
...  
Keyword(s):  
Storm Surge ◽  
Frequency Distribution ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Storm Surges ◽  
The Philippines ◽  
Coastal Areas ◽  
Japan Meteorological Agency ◽  
Series Data

Abstract. A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013 where more than 6000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10 min intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

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