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.

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>

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.

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 Assessing the performance of regional landslide early warning models: the EDuMaP method

2016 ◽  
Vol 16 (1) ◽  
pp. 103-122 ◽  
Author(s):  
M. Calvello ◽  
L. Piciullo
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Model Performance ◽  
Warning System ◽  
Early Warning Systems ◽  
Communication Strategy ◽  
Performance Criteria ◽  
Model Parameters ◽  
Warning Systems ◽  
Warning Model

Abstract. A schematic of the components of regional early warning systems for rainfall-induced landslides is herein proposed, based on a clear distinction between warning models and warning systems. According to this framework an early warning system comprises a warning model as well as a monitoring and warning strategy, a communication strategy and an emergency plan. The paper proposes the evaluation of regional landslide warning models by means of an original approach, called the "event, duration matrix, performance" (EDuMaP) method, comprising three successive steps: identification and analysis of the events, i.e., landslide events and warning events derived from available landslides and warnings databases; definition and computation of a duration matrix, whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model performance by means of performance criteria and indicators applied to the duration matrix. During the first step the analyst identifies and classifies the landslide and warning events, according to their spatial and temporal characteristics, by means of a number of model parameters. In the second step, the analyst computes a time-based duration matrix with a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warning data from the municipal early warning system operating in Rio de Janeiro (Brazil).

scholarly journals A GIS-based monitoring and early warning system for cover-collapse sinkholes in karst terrane in Wuhan, China

2017 ◽  
Author(s):  
Li Xueping ◽  
Xiao Shangde ◽  
Tang Huiming ◽  
Peng Jinsheng
Keyword(s):  
Plastic Zone ◽  
Water Level ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Underground Water ◽  
Water Levels ◽  
Monitoring Data ◽  
Karst Collapse ◽  
Warning Model

Abstract. To reduce disastrous losses caused by karst collapse especially in urban areas, it is important to establish an early warning system utilizing monitoring data. Three major aspects have been monitored based upon engineering geological conditions and characteristics of karst collapse processes in Wuhan, China: changes in surface soil, soil deformation, and groundwater levels. Measurements have been recorded of: (1) soil pressure, (2) ground-penetrating radar images, (3) underground water levels, (4) ground water levels, (5) rainfall, (6) cracking, (7) ground deformation, and (8) water level in monitored wells. This paper has selected geological radar cross-sectional data and underground water level monitoring data to obtain criteria for hydraulic gradient warning, geological radar warning and plastic zone warning based upon these monitoring data and wider knowledge of karst collapse in Wuhan. A comprehensive warning system has been developed on a MAPGIS platform, employing monitoring data in Microsoft Excel format and Microsoft Visual C++ development tools. Three warning levels are adopted by the system: safe, becoming dangerous, and dangerous; indicated in green, yellow and red respectively on hazard maps. The system automatically undertakes processes of data management and model calculation leading to geo-hazard warning map generation. Using monitoring data collected in the first six months of 2011 at Wuhan, the system has established a hydraulic gradient model, plastic zone warning model, geological radar warning model, and a comprehensive early warning model; and has been shown to be an effective method of providing karst collapse warning.

scholarly journals Early Warning System: Solusi Klaim Negatif Rumah Sakit Program Jaminan Kesehatan Nasional

2021 ◽  
Vol 20 (1) ◽  
pp. 12
Author(s):  
Yuki Firmanto
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
System Thinking ◽  
Analysis Model ◽  
Model Framework ◽  
Fast Analysis ◽  
Study Approach ◽  
Hospital Operations ◽  
Warning Model

Hospital bills that are greater than the INA CBGs rate results in losses being charged to the hospital so that it hinders thefulfillment of hospital operational needs. The purpose of this study was to provide an overview of the SIMRS development process by implementing the concept of an early warning system in mitigating BPJS negative claims experienced by RSUD X. The study was conducted at the X Regional General Hospital (RSUD) in Probolinggo. The case study approach was adopted using the data analysis model Framework for the application of systems thinking (FAST). Analysis of the data obtained shows that the existence of BPJS claim information for each patient that can be known in real-time will help mitigate negative claims so as to reduce the risk of loss to the hospital. Referring to this, the resulting output in the form of an early warning system concept was developed using a direct warning model to users with the output of patient billing information. This development can support hospital operations to be effective and efficient. Keywords:  BPJS claims, Early Warning System, Framework for the Application of System Thinking

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