PROPOSED WATER QUALITY SURVEILLANCE NETWORK USING PHYSICAL, CHEMICAL AND BIOLOGICAL EARLY WARNING SYSTEMS (BEWS)

EPA Science Inventory

The Homeland Protection Act of 2002 specifically calls for the investigation and use of Early Warning Systems (EWS) for water security reasons. The EWS is a screening tool for detecting changes in source water and distribution system water quality. A suite of time-relevant biol...

Early warning signals detect critical impacts of experimental warming.

PubMed

Jarvis, Lauren; McCann, Kevin; Tunney, Tyler; Gellner, Gabriel; Fryxell, John M

2016-09-01

Earth's surface temperatures are projected to increase by ~1-4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature-induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

PubMed Central

Brock, William A.; Carpenter, Stephen R.; Ellison, Aaron M.; Livina, Valerie N.; Seekell, David A.; Scheffer, Marten; van Nes, Egbert H.; Dakos, Vasilis

2014-01-01

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data. PMID:24658137

Climate change implications and use of early warning systems for global dust storms

USGS Publications Warehouse

Harriman, Lindsey M.

2014-01-01

With increased changes in land cover and global climate, early detection and warning of dust storms in conjunction with effective and widespread information broadcasts will be essential to the prevention and mitigation of future risks and impacts. Human activities, seasonal variations and long-term climatic patterns influence dust storms. More research is needed to analyse these factors of dust mobilisation to create more certainty for the fate of vulnerable populations and ecosystems in the future. Early warning and communication systems, when in place and effectively implemented, can offer some relief to these vulnerable areas. As an issue that affects many regions of the world, there is a profound need to understand the potential changes and ultimately create better early warning systems for dust storms.

MUSIC algorithm DoA estimation for cooperative node location in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Warty, Chirag; Yu, Richard Wai; ElMahgoub, Khaled; Spinsante, Susanna

In recent years the technological development has encouraged several applications based on distributed communications network without any fixed infrastructure. The problem of providing a collaborative early warning system for multiple mobile nodes against a fast moving object. The solution is provided subject to system level constraints: motion of nodes, antenna sensitivity and Doppler effect at 2.4 GHz and 5.8 GHz. This approach consists of three stages. The first phase consists of detecting the incoming object using a highly directive two element antenna at 5.0 GHz band. The second phase consists of broadcasting the warning message using a low directivity broad antenna beam using 2× 2 antenna array which then in third phase will be detected by receiving nodes by using direction of arrival (DOA) estimation technique. The DOA estimation technique is used to estimate the range and bearing of the incoming nodes. The position of fast arriving object can be estimated using the MUSIC algorithm for warning beam DOA estimation. This paper is mainly intended to demonstrate the feasibility of early detection and warning system using a collaborative node to node communication links. The simulation is performed to show the behavior of detecting and broadcasting antennas as well as performance of the detection algorithm. The idea can be further expanded to implement commercial grade detection and warning system

The effectiveness of physiologically based early warning or track and trigger systems after triage in adult patients presenting to emergency departments: a systematic review.

PubMed

Wuytack, Francesca; Meskell, Pauline; Conway, Aislinn; McDaid, Fiona; Santesso, Nancy; Hickey, Fergal G; Gillespie, Paddy; Raymakers, Adam J N; Smith, Valerie; Devane, Declan

2017-12-06

Changes to physiological parameters precede deterioration of ill patients. Early warning and track and trigger systems (TTS) use routine physiological measurements with pre-specified thresholds to identify deteriorating patients and trigger appropriate and timely escalation of care. Patients presenting to the emergency department (ED) are undiagnosed, undifferentiated and of varying acuity, yet the effectiveness and cost-effectiveness of using early warning systems and TTS in this setting is unclear. We aimed to systematically review the evidence on the use, development/validation, clinical effectiveness and cost-effectiveness of physiologically based early warning systems and TTS for the detection of deterioration in adult patients presenting to EDs. We searched for any study design in scientific databases and grey literature resources up to March 2016. Two reviewers independently screened results and conducted quality assessment. One reviewer extracted data with independent verification of 50% by a second reviewer. Only information available in English was included. Due to the heterogeneity of reporting across studies, results were synthesised narratively and in evidence tables. We identified 6397 citations of which 47 studies and 1 clinical trial registration were included. Although early warning systems are increasingly used in EDs, compliance varies. One non-randomised controlled trial found that using an early warning system in the ED may lead to a change in patient management but may not reduce adverse events; however, this is uncertain, considering the very low quality of evidence. Twenty-eight different early warning systems were developed/validated in 36 studies. There is relatively good evidence on the predictive ability of certain early warning systems on mortality and ICU/hospital admission. No health economic data were identified. Early warning systems seem to predict adverse outcomes in adult patients of varying acuity presenting to the ED but there is a lack of high quality comparative studies to examine the effect of using early warning systems on patient outcomes. Such studies should include health economics assessments.

Vantage point - Early warning flaws.

PubMed

Swinden, Donna

2014-08-28

USING AN EARLY warning score (EWS) system should improve the detection of acutely deteriorating patients. Under such a system, a score is allocated to each of six physiological measurements including respiratory rate and oxygen saturations, which are aggregated to produce an overall score. An aggregated score of seven or higher prompts nursing staff to refer a patient for emergency assessment.

Early warning signals of regime shifts in coupled human–environment systems

PubMed Central

Bauch, Chris T.; Sigdel, Ram; Pharaon, Joe; Anand, Madhur

2016-01-01

In complex systems, a critical transition is a shift in a system’s dynamical regime from its current state to a strongly contrasting state as external conditions move beyond a tipping point. These transitions are often preceded by characteristic early warning signals such as increased system variability. However, early warning signals in complex, coupled human–environment systems (HESs) remain little studied. Here, we compare critical transitions and their early warning signals in a coupled HES model to an equivalent environment model uncoupled from the human system. We parameterize the HES model, using social and ecological data from old-growth forests in Oregon. We find that the coupled HES exhibits a richer variety of dynamics and regime shifts than the uncoupled environment system. Moreover, the early warning signals in the coupled HES can be ambiguous, heralding either an era of ecosystem conservationism or collapse of both forest ecosystems and conservationism. The presence of human feedback in the coupled HES can also mitigate the early warning signal, making it more difficult to detect the oncoming regime shift. We furthermore show how the coupled HES can be “doomed to criticality”: Strategic human interactions cause the system to remain perpetually in the vicinity of a collapse threshold, as humans become complacent when the resource seems protected but respond rapidly when it is under immediate threat. We conclude that the opportunities, benefits, and challenges of modeling regime shifts and early warning signals in coupled HESs merit further research. PMID:27815533

Integrated Land- and Underwater-Based Sensors for a Subduction Zone Earthquake Early Warning System

NASA Astrophysics Data System (ADS)

Pirenne, B.; Rosenberger, A.; Rogers, G. C.; Henton, J.; Lu, Y.; Moore, T.

2016-12-01

Ocean Networks Canada (ONC — oceannetworks.ca/ ) operates cabled ocean observatories off the coast of British Columbia (BC) to support research and operational oceanography. Recently, ONC has been funded by the Province of BC to deliver an earthquake early warning (EEW) system that integrates offshore and land-based sensors to deliver alerts of incoming ground shaking from the Cascadia Subduction Zone. ONC's cabled seismic network has the unique advantage of being located offshore on either side of the surface expression of the subduction zone. The proximity of ONC's sensors to the fault can result in faster, more effective warnings, which translates into more lives saved, injuries avoided and more ability for mitigative actions to take place.ONC delivers near real-time data from various instrument types simultaneously, providing distinct advantages to seismic monitoring and earthquake early warning. The EEW system consists of a network of sensors, located on the ocean floor and on land, that detect and analyze the initial p-wave of an earthquake as well as the crustal deformation on land during the earthquake sequence. Once the p-wave is detected and characterized, software systems correlate the data streams of the various sensors and deliver alerts to clients through a Common Alerting Protocol-compliant data package. This presentation will focus on the development of the earthquake early warning capacity at ONC. It will describe the seismic sensors and their distribution, the p-wave detection algorithms selected and the overall architecture of the system. It will further overview the plan to achieve operational readiness at project completion.

ForWarn Forest Disturbance Change Detection System Provides a Weekly Snapshot of US Forest Conditions to Aid Forest Managers

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Kumar, J.; Hoffman, F. M.

2012-12-01

The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. To help forest and natural resource managers rapidly detect, identify, and respond to unexpected changes in the nation's forests, ForWarn produces sets of national maps showing potential forest disturbances at 231m resolution every 8 days, and posts the results to the web for examination. ForWarn compares current greenness with the "normal," historically seen greenness that would be expected for healthy vegetation for a specific location and time of the year, and then identifies areas appearing less green than expected to provide a strategic national overview of potential forest disturbances that can be used to direct ground and aircraft efforts. In addition to forests, ForWarn also tracks potential disturbances in rangeland vegetation and agriculural crops. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release, and followed by a series of training webinars. Almost 60 early-adopter state and federal forest managers attended at least one of the ForWarn rollout webinars. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the web through the ForWarn Change Assessment Viewer at http://forwarn.forestthreats.org/fcav.

A Neutral Network based Early Eathquake Warning model in California region

NASA Astrophysics Data System (ADS)

Xiao, H.; MacAyeal, D. R.

2016-12-01

Early Earthquake Warning systems could reduce loss of lives and other economic impact resulted from natural disaster or man-made calamity. Current systems could be further enhanced by neutral network method. A 3 layer neural network model combined with onsite method was deployed in this paper to improve the recognition time and detection time for large scale earthquakes.The 3 layer neutral network early earthquake warning model adopted the vector feature design for sample events happened within 150 km radius of the epicenters. Dataset used in this paper contained both destructive events and small scale events. All the data was extracted from IRIS database to properly train the model. In the training process, backpropagation algorithm was used to adjust the weight matrices and bias matrices during each iteration. The information in all three channels of the seismometers served as the source in this model. Through designed tests, it was indicated that this model could identify approximately 90 percent of the events' scale correctly. And the early detection could provide informative evidence for public authorities to make further decisions. This indicated that neutral network model could have the potential to strengthen current early warning system, since the onsite method may greatly reduce the responding time and save more lives in such disasters.

Development of gas fire detection system using tunable diode laser absorption spectroscopy

NASA Astrophysics Data System (ADS)

Jiang, Y. L.; Li, G.; Yang, T.; Wang, J. J.

2017-01-01

The conventional fire detection methods mainly produce an alarm through detecting the changes in smoke concentration, flame radiation, heat and other physical parameters in the environment, but are unable to provide an early warning of a fire emergency. We have designed a gas fire detection system with a high detection sensitivity and high selectivity using the tunable semiconductor diode laser as a light source and combining wavelength modulation and harmonic detection technology. This system can invert the second harmonic signal obtained to obtain the concentration of carbon monoxide gas (a fire characteristic gas) so as to provide an early warning of fire. We reduce the system offset noise and the background noise generated due to the laser interference by deducting the system background spectrum lines from the second harmonic signal. This can also eliminate the interference of other gas spectral lines to a large extent. We detected the concentration of the carbon monoxide gas generated in smoldering sandalwood fire and open beech wood fire with the homemade fire simulator, and tested the lowest detectable limit of system. The test results show that the lowest detectable limit can reach 5×10-6 the system can maintain stable operation for a long period of time and can automatically trigger a water mist fire extinguishing system, which can fully meet the needs of early fire warning.

Response Characteristics of an Aquatic Biomonitor Used for Rapid Toxicity Detection

DTIC Science & Technology

2004-05-15

for drinking water protection. 14. SUBJECT TERMS 15. NUMBER OF PAGES biological early warning system; Lepomis macrochirus; bluegill; aquatic toxicity...Fort Detrick, MD 21702-5010, USA Key words: biomonitor; biological early warning system; Lepomis macrochirus; bluegill; aquatic toxicity; water ...narcosis are most likely to cause rapid aquatic biomonitor depth related to variations in water quality (primarily responses. Other modes of action may

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health

PubMed Central

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-01-01

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient’s cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system. PMID:28353681

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health.

PubMed

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-03-29

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient's cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system.

Sepsis in Obstetrics: Clinical Features and Early Warning Tools.

PubMed

Parfitt, Sheryl E; Bogat, Mary L; Hering, Sandra L; Ottley, Charlotte; Roth, Cheryl

Morbidity and mortality associated with sepsis has gained widespread attention on a local, state, and national level, yet, it remains a complicated disorder that can be difficult to identify in a timely manner. Sepsis in obstetric patients further complicates the diagnosis as alterations in physiology related to pregnancy can mask sepsis indicators normally seen in the general population. If early signs of sepsis go unrecognized, septic shock can develop, leading to organ dysfunction and potential death. Maternal early warning tools have been designed to assist clinicians in recognizing early indications of illness. Through use of clinical pathway-specific tools, disease processes may be detected early, subsequently benefitting patients with aggressive treatment management and intervention.This article is the second in a series of three that discuss the importance of sepsis and septic shock in pregnancy. Risk factors, causes of sepsis, signs and symptoms, and maternal early warning tools are discussed.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

PubMed Central

Dakos, Vasilis; Carpenter, Stephen R.; Brock, William A.; Ellison, Aaron M.; Guttal, Vishwesha; Ives, Anthony R.; Kéfi, Sonia; Livina, Valerie; Seekell, David A.; van Nes, Egbert H.; Scheffer, Marten

2012-01-01

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data. PMID:22815897

Early Warning/Track-and-Trigger Systems to Detect Deterioration and Improve Outcomes in Hospitalized Patients.

PubMed

Shiloh, Ariel L; Lominadze, George; Gong, Michelle N; Savel, Richard H

2016-02-01

As a global effort toward improving patient safety, a specific area of focus has been the early recognition and rapid intervention in deteriorating ward patients. This focus on "failure to rescue" has led to the construction of early warning/track-and-trigger systems. In this review article, we present a description of the data behind the creation and implementation of such systems, including multiple algorithms and strategies for deployment. Additionally, the strengths and weaknesses of the various systems and their evaluation in the literature are emphasized. Despite the limitations of the current literature, the potential benefit of these early warning/track-and-trigger systems to improve patient outcomes remains significant. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Packaging: a grounded theory of how to report physiological deterioration effectively.

PubMed

Andrews, Tom; Waterman, Heather

2005-12-01

The aim of this paper is to present a study of how ward-based staff use vital signs and the Early Warning Score to package physiological deterioration effectively to ensure successful referral to doctors. The literature tends to emphasize the identification of premonitory signs in predicting physiological deterioration. However, these signs lack sensitivity and specificity, and there is evidence that nurses rely on subjective and subtle indicators. The Early Warning Score was developed for the early detection of deterioration and has been widely implemented, with various modifications. The data reported here form part of a larger study investigating the practical problems faced by general ward staff in detecting physiological deterioration. During 2002, interviews and observations were carried out using a grounded theory approach, and a total of 44 participants were interviewed (30 nurses, 7 doctors and 7 health care support workers). Participants reported that quantifiable evidence is the most effective means of referring patients to doctors, and the Early Warning Score achieves this by improving communication between professionals. Rather than reporting changes in individual vital signs, the Early Warning Score effectively packages them together, resulting in a much more convincing referral. It gives nurses a precise, concise and unambiguous means of communicating deterioration, and confidence in using medical language. Thus, nurses are empowered and doctors can focus quickly on identified problems. The Early Warning Score leads to successful referral of patients by providing an agreed framework for assessment, increasing confidence in the use of medical language and empowering nurses. It is essential that nurses and nursing students are supported in its use and in developing confidence in using medical language by continued emphasis on physiology and pathophysiology in the nursing curriculum.

Studying the response of drivers against different collision warning systems: a review

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.

Detection of Deteriorating Patients on Surgical Wards Outside the ICU by an Automated MEWS-Based Early Warning System With Paging Functionality.

PubMed

Heller, Axel R; Mees, Sören T; Lauterwald, Benjamin; Reeps, Christian; Koch, Thea; Weitz, Jürgen

2018-05-16

The establishment of early warning systems in hospitals was strongly recommended in recent guidelines to detect deteriorating patients early and direct them to adequate care. Upon reaching predefined trigger criteria, Medical Emergency Teams (MET) should be notified and directed to these patients. The present study analyses the effect of introducing an automated multiparameter early warning score (MEWS)-based early warning system with paging functionality on 2 wards hosting patients recovering from highly complex surgical interventions. The deployment of the system was accompanied by retrospective data acquisition during 12 months (intervention) using 4 routine databases: Hospital patient data management, anesthesia database, local data of the German Resuscitation Registry, and measurement logs of the deployed system (intervention period only). A retrospective 12-month data review using the same aforementioned databases before the deployment of the system served as control. Control and intervention phases were separated by a 6-month washout period for the installation of the system and for training. Data from 3827 patients could be acquired from 2 surgical wards during the two 12-month periods, 1896 patients in the control and 1931 in the intervention cohorts. Patient characteristics differed between the 2 observation phases. American Society of Anesthesiologists risk classification and duration of surgery as well as German DRG case-weight were significantly higher in the intervention period. However, the rate of cardiac arrests significantly dropped from 5.3 to 2.1 per 1000 admissions in the intervention period (P < 0.001). This observation was paralleled by a reduction of unplanned ICU admissions from 3.6% to 3.0% (P < 0.001), and an increase of notifications of critical conditions to the ward surgeon. The primary triggers for MET activation were abnormal ECG alerts, specifically asystole (n = 5), and pulseless electric activity (n = 8). In concert with a well-trained and organized MET, the early deterioration detection of patients on surgical wards outside the ICU may be improved by introducing an automated MEWS-based early warning system with paging functionality.

An early warning system for groundwater pollution based on the assessment of groundwater pollution risks.

NASA Astrophysics Data System (ADS)

Zhang, Weihong.; Zhao, Yongsheng; Hong, Mei; Guo, Xiaodong

2009-04-01

Groundwater pollution usually is complex and concealed, remediation of which is difficult, high cost, time-consuming, and ineffective. An early warning system for groundwater pollution is needed that detects groundwater quality problems and gets the information necessary to make sound decisions before massive groundwater quality degradation occurs. Groundwater pollution early warning were performed by considering comprehensively the current groundwater quality, groundwater quality varying trend and groundwater pollution risk . The map of the basic quality of the groundwater was obtained by fuzzy comprehensive evaluation or BP neural network evaluation. Based on multi-annual groundwater monitoring datasets, Water quality state in sometime of the future was forecasted using time-sequenced analyzing methods. Water quality varying trend was analyzed by Spearman's rank correlative coefficient.The relative risk map of groundwater pollution was estimated through a procedure that identifies, cell by cell,the values of three factors, that is inherent vulnerability, load risk of pollution source and contamination hazard. DRASTIC method was used to assess inherent vulnerability of aquifer. Load risk of pollution source was analyzed based on the potential of contamination and pollution degree. Assessment index of load risk of pollution source which involves the variety of pollution source, quantity of contaminants, releasing potential of pollutants, and distance were determined. The load risks of all sources considered by GIS overlay technology. Early warning model of groundwater pollution combined with ComGIS technology organically, the regional groundwater pollution early-warning information system was developed, and applied it into Qiqiha'er groundwater early warning. It can be used to evaluate current water quality, to forecast water quality changing trend, and to analyze space-time influencing range of groundwater quality by natural process and human activities. Keywords: groundwater pollution, early warning, aquifer vulnerability, pollution load, pollution risk, ComGIS

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013.

PubMed

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet; Nilles, Eric

2014-11-01

On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Almost 40% of the Santa Cruz Islands' population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities.

GPS water level measurements for Indonesia's Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Schöne, T.; Pandoe, W.; Mudita, I.; Roemer, S.; Illigner, J.; Zech, C.; Galas, R.

2011-03-01

On Boxing Day 2004, a severe tsunami was generated by a strong earthquake in Northern Sumatra causing a large number of casualties. At this time, neither an offshore buoy network was in place to measure tsunami waves, nor a system to disseminate tsunami warnings to local governmental entities. Since then, buoys have been developed by Indonesia and Germany, complemented by NOAA's Deep-ocean Assessment and Reporting of Tsunamis (DART) buoys, and have been moored offshore Sumatra and Java. The suite of sensors for offshore tsunami detection in Indonesia has been advanced by adding GPS technology for water level measurements. The usage of GPS buoys in tsunami warning systems is a relatively new approach. The concept of the German Indonesian Tsunami Early Warning System (GITEWS) (Rudloff et al., 2009) combines GPS technology and ocean bottom pressure (OBP) measurements. Especially for near-field installations where the seismic noise may deteriorate the OBP data, GPS-derived sea level heights provide additional information. The GPS buoy technology is precise enough to detect medium to large tsunamis of amplitudes larger than 10 cm. The analysis presented here suggests that for about 68% of the time, tsunamis larger than 5 cm may be detectable.

Detecting spatial regimes in ecosystems

EPA Science Inventory

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological ...

Signature-forecasting and early outbreak detection system

PubMed Central

Naumova, Elena N.; MacNeill, Ian B.

2008-01-01

SUMMARY Daily disease monitoring via a public health surveillance system provides valuable information on population risks. Efficient statistical tools for early detection of rapid changes in the disease incidence are a must for modern surveillance. The need for statistical tools for early detection of outbreaks that are not based on historical information is apparent. A system is discussed for monitoring cases of infections with a view to early detection of outbreaks and to forecasting the extent of detected outbreaks. We propose a set of adaptive algorithms for early outbreak detection that does not rely on extensive historical recording. We also include knowledge of infection disease epidemiology into forecasts. To demonstrate this system we use data from the largest water-borne outbreak of cryptosporidiosis, which occurred in Milwaukee in 1993. Historical data are smoothed using a loess-type smoother. Upon receipt of a new datum, the smoothing is updated and estimates are made of the first two derivatives of the smooth curve, and these are used for near-term forecasting. Recent data and the near-term forecasts are used to compute a color-coded warning index, which quantify the level of concern. The algorithms for computing the warning index have been designed to balance Type I errors (false prediction of an epidemic) and Type II errors (failure to correctly predict an epidemic). If the warning index signals a sufficiently high probability of an epidemic, then a forecast of the possible size of the outbreak is made. This longer term forecast is made by fitting a ‘signature’ curve to the available data. The effectiveness of the forecast depends upon the extent to which the signature curve captures the shape of outbreaks of the infection under consideration. PMID:18716671

Assessment of early warning system performance and improvements since it is in operational phase in Romania

NASA Astrophysics Data System (ADS)

Ionescu, Constantin; Marmureanu, Alexandru; Marmureanu, Gheorghe; Ortansa Cioflan, Carmen

2017-04-01

Earthquake represents a major natural disaster for Romanian territory. The main goal following the occurrence of a strong earthquake is to minimize the total number of fatalities. A rapid early warning system (REWS) was developed in Romania in order to provide 25-35 seconds warning time to Bucharest facilities for the earthquakes with M>5.0. The system consists of four components: a network of strong motion sensors installed in the epicentral area, a redundant communication network, an automatic analyzing system located in the Romanian Data Centre and an alert distribution system. The detection algorithm is based on the magnitude computation using strong motion data and rapid evaluation and scaling relation between the maximum P-wave acceleration measured in the epicentral area and the higher ground motion amplitude recorded in Bucharest. In order to reduce the damages caused by earthquakes, the exploitation of the up to date technology is very important. The information is the key point in the disaster management, and the internet is one of the most used instrument, implying also low costs. The Rapid Early Warning System was expanded to cover all countries affected by major earthquakes originating in the Vrancea seismic area and reduce their impact on existing installations of national interest in neighbouring Romania and elsewhere. REWS provides an efficient instrument for prevention and reaction based on the integrated system for seismic detection in South-Eastern Europe. REWS has been operational since 2013 and sends alert the authorities, hazardous facilities in Romania and Bulgaria (NPP, emergency response agencies etc.) and to public via twitter and some smartphone applications developed in the house. Also, NIEP is part of the UNESCO initiative case on developing a platform on earthquake early warning systems (IP-MEP) that aims to promote and strengthen the development of earthquake early warning systems in earthquake-prone regions of the world by sharing scientific knowledge, capacity building and international cooperation.

Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

101. View of transmitter building no. 102, missile warning operation ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

101. View of transmitter building no. 102, missile warning operation center, close up view of DRED (detection radar environmental display) console in operation showing target. Official photograph BMEWS Project by Hansen, 14 March 1963, clear as negative no. A-8803. - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Electric Field Sensor for Lightning Early Warning System

NASA Astrophysics Data System (ADS)

Premlet, B.; Mohammed, R.; Sabu, S.; Joby, N. E.

2017-12-01

Electric field mills are used popularly for atmospheric electric field measurements. Atmospheric Electric Field variation is the primary signature for Lightning Early Warning systems. There is a characteristic change in the atmospheric electric field before lightning during a thundercloud formation.A voltage controlled variable capacitance is being proposed as a method for non-contacting measurement of electric fields. A varactor based mini electric field measurement system is developed, to detect any change in the atmospheric electric field and to issue lightning early warning system. Since this is a low-cost device, this can be used for developing countries which are facing adversities. A network of these devices can help in forming a spatial map of electric field variations over a region, and this can be used for more improved atmospheric electricity studies in developing countries.

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013

PubMed Central

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet

2014-01-01

Abstract Problem On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. Approach A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Local setting Almost 40% of the Santa Cruz Islands’ population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. Relevant changes By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. Lesson learnt It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities. PMID:25378746

Implementing drought early warning systems: policy lessons and future needs

NASA Astrophysics Data System (ADS)

Iglesias, Ana; Werner, Micha; Maia, Rodrigo; Garrote, Luis; Nyabeze, Washington

2014-05-01

Drought forecasting and Warning provides the potential of reducing impacts to society due to drought events. The implementation of effective drought forecasting and warning, however, requires not only science to support reliable forecasting, but also adequate policy and societal response. Here we propose a protocol to develop drought forecasting and early warning based in the international cooperation of African and European institutions in the DEWFORA project (EC, 7th Framework Programme). The protocol includes four major phases that address the scientific knowledge and the social capacity to use the knowledge: (a) What is the science available? Evaluating how signs of impending drought can be detected and predicted, defining risk levels, and analysing of the signs of drought in an integrated vulnerability approach. (b) What are the societal capacities? In this the institutional framework that enables policy development is evaluated. The protocol gathers information on vulnerability and pending hazard in advance so that early warnings can be declared at sufficient lead time and drought mitigation planning can be implemented at an early stage. (c) How can science be translated into policy? Linking science indicators into the actions/interventions that society needs to implement, and evaluating how policy is implemented. Key limitations to planning for drought are the social capacities to implement early warning systems. Vulnerability assessment contributes to identify these limitations and therefore provides crucial information to policy development. Based on the assessment of vulnerability we suggest thresholds for management actions to respond to drought forecasts and link predictive indicators to relevant potential mitigation strategies. Vulnerability assessment is crucial to identify relief, coping and management responses that contribute to a more resilient society. (d) How can society benefit from the forecast? Evaluating how information is provided to potentially affected groups, and how mitigation strategies can be taken in response. This paper presents an outline of the protocol that was developed in the DEWFORA project, outlining the complementary roles of science, policy and societal uptake in effective drought forecasting and warning. A consensus on the need to emphasise the social component of early warning was reached when testing the DEWFORA early warning system protocol among experts from 18 countries.

Detection of pathogenic viruses in sewage provided early warnings of hepatitis A virus and norovirus outbreaks.

PubMed

Hellmér, Maria; Paxéus, Nicklas; Magnius, Lars; Enache, Lucica; Arnholm, Birgitta; Johansson, Annette; Bergström, Tomas; Norder, Heléne

2014-11-01

Most persons infected with enterically transmitted viruses shed large amounts of virus in feces for days or weeks, both before and after onset of symptoms. Therefore, viruses causing gastroenteritis may be detected in wastewater, even if only a few persons are infected. In this study, the presence of eight pathogenic viruses (norovirus, astrovirus, rotavirus, adenovirus, Aichi virus, parechovirus, hepatitis A virus [HAV], and hepatitis E virus) was investigated in sewage to explore whether their identification could be used as an early warning of outbreaks. Samples of the untreated sewage were collected in proportion to flow at Ryaverket, Gothenburg, Sweden. Daily samples collected during every second week between January and May 2013 were pooled and analyzed for detection of viruses by concentration through adsorption to milk proteins and PCR. The largest amount of noroviruses was detected in sewage 2 to 3 weeks before most patients were diagnosed with this infection in Gothenburg. The other viruses were detected at lower levels. HAV was detected between weeks 5 and 13, and partial sequencing of the structural VP1protein identified three different strains. Two strains were involved in an ongoing outbreak in Scandinavia and were also identified in samples from patients with acute hepatitis A in Gothenburg during spring of 2013. The third strain was unique and was not detected in any patient sample. The method used may thus be a tool to detect incipient outbreaks of these viruses and provide early warning before the causative pathogens have been recognized in health care. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Detection of Pathogenic Viruses in Sewage Provided Early Warnings of Hepatitis A Virus and Norovirus Outbreaks

PubMed Central

Hellmér, Maria; Paxéus, Nicklas; Magnius, Lars; Enache, Lucica; Arnholm, Birgitta; Johansson, Annette; Bergström, Tomas

2014-01-01

Most persons infected with enterically transmitted viruses shed large amounts of virus in feces for days or weeks, both before and after onset of symptoms. Therefore, viruses causing gastroenteritis may be detected in wastewater, even if only a few persons are infected. In this study, the presence of eight pathogenic viruses (norovirus, astrovirus, rotavirus, adenovirus, Aichi virus, parechovirus, hepatitis A virus [HAV], and hepatitis E virus) was investigated in sewage to explore whether their identification could be used as an early warning of outbreaks. Samples of the untreated sewage were collected in proportion to flow at Ryaverket, Gothenburg, Sweden. Daily samples collected during every second week between January and May 2013 were pooled and analyzed for detection of viruses by concentration through adsorption to milk proteins and PCR. The largest amount of noroviruses was detected in sewage 2 to 3 weeks before most patients were diagnosed with this infection in Gothenburg. The other viruses were detected at lower levels. HAV was detected between weeks 5 and 13, and partial sequencing of the structural VP1protein identified three different strains. Two strains were involved in an ongoing outbreak in Scandinavia and were also identified in samples from patients with acute hepatitis A in Gothenburg during spring of 2013. The third strain was unique and was not detected in any patient sample. The method used may thus be a tool to detect incipient outbreaks of these viruses and provide early warning before the causative pathogens have been recognized in health care. PMID:25172863

Early Intervention: How Parents Can Help Adolescent Children Who May Be Using Drugs.

ERIC Educational Resources Information Center

Franklin, Diane, Ed.; Bankston, Karen, Ed.

The earlier a parent can detect and respond to a child's involvement with alcohol and other drugs (AOD), the better. Just as early detection heightens the cure rate for cancer, so too does early intervention increase the chances of ending AOD use. This booklet outlines warning signs of AOD use and lists the hazards of adolescent drug use.…

Personal Cabin Pressure Monitor and Warning System

NASA Technical Reports Server (NTRS)

Zysko, Jan A. (Inventor)

2002-01-01

A cabin pressure altitude monitor and warning system provides a warning when a detected cabin pressure altitude has reached a predetermined level. The system is preferably embodied in a portable, pager-sized device that can be carried or worn by an individual. A microprocessor calculates the pressure altitude from signals generated by a calibrated pressure transducer and a temperature sensor that compensates for temperature variations in the signals generated by the pressure transducer. The microprocessor is programmed to generate a warning or alarm if a cabin pressure altitude exceeding a predetermined threshold is detected. Preferably, the microprocessor generates two different types of warning or alarm outputs, a first early warning or alert when a first pressure altitude is exceeded. and a second more serious alarm condition when either a second. higher pressure altitude is exceeded, or when the first pressure altitude has been exceeded for a predetermined period of time. Multiple types of alarm condition indicators are preferably provided, including visual, audible and tactile. The system is also preferably designed to detect gas concentrations and other ambient conditions, and thus incorporates other sensors, such as oxygen, relative humidity, carbon dioxide, carbon monoxide and ammonia sensors, to provide a more complete characterization and monitoring of the local environment.

Personal Cabin Pressure Monitor and Warning System

NASA Astrophysics Data System (ADS)

Zysko, Jan A.

2002-09-01

A cabin pressure altitude monitor and warning system provides a warning when a detected cabin pressure altitude has reached a predetermined level. The system is preferably embodied in a portable, pager-sized device that can be carried or worn by an individual. A microprocessor calculates the pressure altitude from signals generated by a calibrated pressure transducer and a temperature sensor that compensates for temperature variations in the signals generated by the pressure transducer. The microprocessor is programmed to generate a warning or alarm if a cabin pressure altitude exceeding a predetermined threshold is detected. Preferably, the microprocessor generates two different types of warning or alarm outputs, a first early warning or alert when a first pressure altitude is exceeded. and a second more serious alarm condition when either a second. higher pressure altitude is exceeded, or when the first pressure altitude has been exceeded for a predetermined period of time. Multiple types of alarm condition indicators are preferably provided, including visual, audible and tactile. The system is also preferably designed to detect gas concentrations and other ambient conditions, and thus incorporates other sensors, such as oxygen, relative humidity, carbon dioxide, carbon monoxide and ammonia sensors, to provide a more complete characterization and monitoring of the local environment.

[The application of the prospective space-time statistic in early warning of infectious disease].

PubMed

Yin, Fei; Li, Xiao-Song; Feng, Zi-Jian; Ma, Jia-Qi

2007-06-01

To investigate the application of prospective space-time scan statistic in the early stage of detecting infectious disease outbreaks. The prospective space-time scan statistic was tested by mimicking daily prospective analyses of bacillary dysentery data of Chengdu city in 2005 (3212 cases in 102 towns and villages). And the results were compared with that of purely temporal scan statistic. The prospective space-time scan statistic could give specific messages both in spatial and temporal. The results of June indicated that the prospective space-time scan statistic could timely detect the outbreaks that started from the local site, and the early warning message was powerful (P = 0.007). When the merely temporal scan statistic for detecting the outbreak was sent two days later, and the signal was less powerful (P = 0.039). The prospective space-time scan statistic could make full use of the spatial and temporal information in infectious disease data and could timely and effectively detect the outbreaks that start from the local sites. The prospective space-time scan statistic could be an important tool for local and national CDC to set up early detection surveillance systems.

Devising a method towards development of early warning tool for detection of malaria outbreak.

PubMed

Verma, Preeti; Sarkar, Soma; Singh, Poonam; Dhiman, Ramesh C

2017-11-01

Uncertainty often arises in differentiating seasonal variation from outbreaks of malaria. The present study was aimed to generalize the theoretical structure of sine curve for detecting an outbreak so that a tool for early warning of malaria may be developed. A 'case/mean-ratio scale' system was devised for labelling the outbreak in respect of two diverse districts of Assam and Rajasthan. A curve-based method of analysis was developed for determining outbreak and using the properties of sine curve. It could be used as an early warning tool for Plasmodium falciparum malaria outbreaks. In the present method of analysis, the critical C max (peak value of sine curve) value of seasonally adjusted curve for P. falciparum malaria outbreak was 2.3 for Karbi Anglong and 2.2 for Jaisalmer districts. On case/mean-ratio scale, the C max value of malaria curve between C max and 3.5, the outbreak could be labelled as minor while >3.5 may be labelled as major. In epidemic years, with mean of case/mean ratio of ≥1.00 and root mean square (RMS) ≥1.504 of case/mean ratio, outbreaks can be predicted 1-2 months in advance. The present study showed that in P. falciparum cases in Karbi Anglong (Assam) and Jaisalmer (Rajasthan) districts, the rise in C max value of curve was always followed by rise in average/RMS or both and hence could be used as an early warning tool. The present method provides better detection of outbreaks than the conventional method of mean plus two standard deviation (mean+2 SD). The identified tools are simple and may be adopted for preparedness of malaria outbreaks.

Research on capability of detecting ballistic missile by near space infrared system

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Jiang, Wei; Jiang, Feng

2018-01-01

The infrared detection technology of ballistic missile based on near space platform can effectively make up the shortcomings of high-cost of traditional early warning satellites and the limited earth curvature of ground-based early warning radar. In terms of target detection capability, aiming at the problem that the formula of the action distance based on contrast performance ignores the background emissivity in the calculation process and the formula is only valid for the monochromatic light, an improved formula of the detecting range based on contrast performance is proposed. The near space infrared imaging system parameters are introduced, the expression of the contrastive action distance formula based on the target detection of the near space platform is deduced. The detection range of the near space infrared system for the booster stage ballistic missile skin, the tail nozzle and the tail flame is calculated. The simulation results show that the near-space infrared system has the best effect on the detection of tail-flame radiation.

Experiences integrating autonomous components and legacy systems into tsunami early warning systems

NASA Astrophysics Data System (ADS)

Reißland, S.; Herrnkind, S.; Guenther, M.; Babeyko, A.; Comoglu, M.; Hammitzsch, M.

2012-04-01

Fostered by and embedded in the general development of Information and Communication Technology (ICT) the evolution of Tsunami Early Warning Systems (TEWS) shows a significant development from seismic-centred to multi-sensor system architectures using additional sensors, e.g. sea level stations for the detection of tsunami waves and GPS stations for the detection of ground displacements. Furthermore, the design and implementation of a robust and scalable service infrastructure supporting the integration and utilisation of existing resources serving near real-time data not only includes sensors but also other components and systems offering services such as the delivery of feasible simulations used for forecasting in an imminent tsunami threat. In the context of the development of the German Indonesian Tsunami Early Warning System (GITEWS) and the project Distant Early Warning System (DEWS) a service platform for both sensor integration and warning dissemination has been newly developed and demonstrated. In particular, standards of the Open Geospatial Consortium (OGC) and the Organization for the Advancement of Structured Information Standards (OASIS) have been successfully incorporated. In the project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC) new developments are used to extend the existing platform to realise a component-based technology framework for building distributed TEWS. This talk will describe experiences made in GITEWS, DEWS and TRIDEC while integrating legacy stand-alone systems and newly developed special-purpose software components into TEWS using different software adapters and communication strategies to make the systems work together in a corporate infrastructure. The talk will also cover task management and data conversion between the different systems. Practical approaches and software solutions for the integration of sensors, e.g. providing seismic and sea level data, and utilisation of special-purpose components, such as simulation systems, in TEWS will be presented.

Vital signs and other observations used to detect deterioration in pregnant women: an analysis of vital sign charts in consultant-led UK maternity units.

PubMed

Smith, G B; Isaacs, R; Andrews, L; Wee, M Y K; van Teijlingen, E; Bick, D E; Hundley, V

2017-05-01

Obstetric early warning systems are recommended for monitoring hospitalised pregnant and postnatal women. We decided to compare: (i) vital sign values used to define physiological normality; (ii) symptoms and signs used to escalate care; (iii) type of chart used; and (iv) presence of explicit instructions for escalating care. One-hundred-and-twenty obstetric early warning charts and escalation protocols were obtained from consultant-led maternity units in the UK and Channel Islands. These data were extracted: values used to determine normality for each maternal vital sign; chart colour-coding; instructions following early warning system triggering; other criteria used as triggers. There was considerable variation in the charts, warning systems and escalation protocols. Of 120 charts, 89.2% used colour; 69.2% used colour-coded escalation systems. Forty-one (34.2%) systems required the calculation of weighted scores. Seventy-five discrete combinations of 'normal' vital sign ranges were found, the most common being: heart rate=50-99beats/min; respiratory rate=11-20breaths/min; blood pressure, systolic=100-149mmHg, diastolic ≤89mmHg; SpO 2 =95-100%; temperature=36.0-37.9°C; and Alert-Voice-Pain-Unresponsive assessment=Alert. Most charts (90.8%) provided instructions about who to contact following triggering, but only 41.7% gave instructions about subsequent observation frequency. The wide range of 'normal' vital sign values in different systems suggests a lack of equity in the processes for detecting deterioration and escalating care in hospitalised pregnant and postnatal women. Agreement regarding 'normal' vital sign ranges is urgently required and would assist the development of a standardised obstetric early warning system and chart. Copyright © 2017 Elsevier Ltd. All rights reserved.

Role of remote sensing in desert locust early warning

NASA Astrophysics Data System (ADS)

Cressman, Keith

2013-01-01

Desert locust (Schistocerca gregaria, Forskål) plagues have historically had devastating consequences on food security in Africa and Asia. The current strategy to reduce the frequency of plagues and manage desert locust infestations is early warning and preventive control. To achieve this, the Food and Agriculture Organization of the United Nations operates one of the oldest, largest, and best-known migratory pest monitoring systems in the world. Within this system, remote sensing plays an important role in detecting rainfall and green vegetation. Despite recent technological advances in data management and analysis, communications, and remote sensing, monitoring desert locusts and preventing plagues in the years ahead will continue to be a challenge from a geopolitical and financial standpoint for affected countries and the international donor community. We present an overview of the use of remote sensing in desert locust early warning.

Tsunami Early Warning via a Physics-Based Simulation Pipeline

NASA Astrophysics Data System (ADS)

Wilson, J. M.; Rundle, J. B.; Donnellan, A.; Ward, S. N.; Komjathy, A.

2017-12-01

Through independent efforts, physics-based simulations of earthquakes, tsunamis, and atmospheric signatures of these phenomenon have been developed. With the goal of producing tsunami forecasts and early warning tools for at-risk regions, we join these three spheres to create a simulation pipeline. The Virtual Quake simulator can produce thousands of years of synthetic seismicity on large, complex fault geometries, as well as the expected surface displacement in tsunamigenic regions. These displacements are used as initial conditions for tsunami simulators, such as Tsunami Squares, to produce catalogs of potential tsunami scenarios with probabilities. Finally, these tsunami scenarios can act as input for simulations of associated ionospheric total electron content, signals which can be detected by GNSS satellites for purposes of early warning in the event of a real tsunami. We present the most recent developments in this project.

How to select a proper early warning threshold to detect infectious disease outbreaks based on the China infectious disease automated alert and response system (CIDARS).

PubMed

Wang, Ruiping; Jiang, Yonggen; Michael, Engelgau; Zhao, Genming

2017-06-12

China Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005. The CIDARS was used to strengthen infectious disease surveillance and aid in the early warning of outbreak. The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDC at all levels in China. Early warning threshold is crucial for outbreak detection in the CIDARS, but CDCs at all level are currently using thresholds recommended by the China CDC, and these recommended thresholds have recognized limitations. Our study therefore seeks to explore an operational method to select the proper early warning threshold according to the epidemic features of local infectious diseases. The data used in this study were extracted from the web-based Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS), and data for infectious disease cases were organized by calendar week (1-52) and year (2009-2015) in Excel format; Px was calculated using a percentile-based moving window (moving window [5 week*5 year], x), where x represents one of 12 centiles (0.40, 0.45, 0.50….0.95). Outbreak signals for the 12 Px were calculated using the moving percentile method (MPM) based on data from the CIDARS. When the outbreak signals generated by the 'mean + 2SD' gold standard were in line with a Px generated outbreak signal for each week during the year of 2014, this Px was then defined as the proper threshold for the infectious disease. Finally, the performance of new selected thresholds for each infectious disease was evaluated by simulated outbreak signals based on 2015 data. Six infectious diseases were selected in this study (chickenpox, mumps, hand foot and mouth diseases (HFMD), scarlet fever, influenza and rubella). Proper thresholds for chickenpox (P75), mumps (P80), influenza (P75), rubella (P45), HFMD (P75), and scarlet fever (P80) were identified. The selected proper thresholds for these 6 infectious diseases could detect almost all simulated outbreaks within a shorter time period compared to thresholds recommended by the China CDC. It is beneficial to select the proper early warning threshold to detect infectious disease aberrations based on characteristics and epidemic features of local diseases in the CIDARS.

Real-Time Integration of Positioning and Accelerometer Data for Early Earthquake Warning on Canada's West Coast

NASA Astrophysics Data System (ADS)

Biffard, B.; Rosenberger, A.; Pirenne, B.; Valenzuela, M.; MacArthur, M.

2017-12-01

Ocean Networks Canada (ONC) operates ocean and coastal observatories on all three of Canada's coasts, and more particularly across the Cascadia subduction zone. The data are acquired, parsed, calibrated and archived by ONC's data management system (Oceans 2.0), with real-time event detection, reaction and access capabilities. As such, ONC is in a unique position to develop early warning systems for earthquakes, near- and far-field tsunamis and other events. ONC is leading the development of a system to alert southwestern British Columbia of an impending Cascadia subduction zone earthquake on behalf of the provincial government and with the support of the Canadian Federal Government. Similarly to other early earthquake warning systems, an array of accelerometers is used to detect the initial earthquake p-waves. This can provide 5-60 seconds of warning to subscribers who can then take action, such as stopping trains and surgeries, closing valves, taking cover, etc. To maximize the detection capability and the time available to react to a notification, instruments are placed both underwater and on land on Vancouver Island. A novel feature of ONC's system is, for land-based sites, the combination of real-time satellite positioning (GNSS) and accelerometer data in the calculations to improve earthquake intensity estimates. This results in higher accuracy, dynamic range and responsiveness than either type of sensor is capable of alone. P-wave detections and displacement data are sent from remote stations to a data centre that must calculate epicentre locations and magnitude. The latter are then delivered to subscribers with client software that, given their position, will calculate arrival time and intensity. All of this must occur with very high standards for latency, reliability and accuracy.

Sinkhole monitoring and early warning: An experimental and successful GB-InSAR application

NASA Astrophysics Data System (ADS)

Intrieri, Emanuele; Gigli, Giovanni; Nocentini, Massimiliano; Lombardi, Luca; Mugnai, Francesco; Fidolini, Francesco; Casagli, Nicola

2015-07-01

Sinkholes represent a natural risk that may hit catastrophically without clearly detectible precursors. However, they are often overlooked by people and administrators. Therefore sinkhole monitoring and associated early warnings constitute important research topics but, currently, only a few papers about sinkhole prediction can be found. In this paper an experience of sinkhole monitoring and early warning with GB-InSAR is described. The latter is a highly precise instrument that is able to produce displacement maps with metric spatial resolution. The described activities were carried out on Elba Island (central Italy), where karstified limestone set off the occurrence of nine sinkholes since 2008, all within less than 3000 m2, causing major damage to an important road and many indirect losses. In 1 year of monitoring two deforming areas were detected, and the point where a sinkhole was about to propagate to the street level was predicted, thus permitting the preventive closure of the road. The deformation area was larger than the hole generated by the sinkhole, thus showing a subsidence that continued for a prolonged time even after the cavity was filled up. The occurrence of a 1.5-m-wide sinkhole, undetected by the GB-InSAR, also showed the lower detection limit of the instrument.

Probabilistic and Evolutionary Early Warning System: concepts, performances, and case-studies

NASA Astrophysics Data System (ADS)

Zollo, A.; Emolo, A.; Colombelli, S.; Elia, L.; Festa, G.; Martino, C.; Picozzi, M.

2013-12-01

PRESTo (PRobabilistic and Evolutionary early warning SysTem) is a software platform for Earthquake Early Warning that integrates algorithms for real-time earthquake location, magnitude estimation and damage assessment into a highly configurable and easily portable package. In its regional configuration, the software processes, in real-time, the 3-component acceleration data streams coming from seismic stations, for P-waves arrival detection and, in the case a quite large event is occurring, can promptly performs event detection and location, magnitude estimation and peak ground-motion prediction at target sites. The regional approach has been integrated with a threshold-based early warning method that allows, in the very first seconds after a moderate-to-large earthquake, to identify the most Probable Damaged Zone starting from the real-time measurement at near-source stations located at increasing distances from the earthquake epicenter, of the peak displacement (Pd) and predominant period of P-waves (τc), over a few-second long window after the P-wave arrival. Thus, each recording site independently provides an evolutionary alert level, according to the Pd and τc it measured, through a decisional table. Since 2009, PRESTo has been under continuous real-time testing using data streaming from the Iripinia Seismic Network (Southern Italy) and has produced a bulletin of some hundreds low magnitude events, including all the M≥2.5 earthquakes occurred in that period in Irpinia. Recently, PRESTo has been also implemented at the accelerometric network and broad-band networks in South Korea and in Romania, and off-line tested in Iberian Peninsula, in Turkey, in Israel, and in Japan. The feasibility of an Early Warning System at national scale, is currently under testing by studying the performances of the PRESTo platform for the Italian Accelerometric Network. Moreover, PRESTo is under experimentation in order to provide alert in a high-school located in the neighborhood of Naples at about 100 km from the Irpinia region.

Early warning of changing drinking water quality by trend analysis.

PubMed

Tomperi, Jani; Juuso, Esko; Leiviskä, Kauko

2016-06-01

Monitoring and control of water treatment plants play an essential role in ensuring high quality drinking water and avoiding health-related problems or economic losses. The most common quality variables, which can be used also for assessing the efficiency of the water treatment process, are turbidity and residual levels of coagulation and disinfection chemicals. In the present study, the trend indices are developed from scaled measurements to detect warning signs of changes in the quality variables of drinking water and some operating condition variables that strongly affect water quality. The scaling is based on monotonically increasing nonlinear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. Deviation indices are used to assess the severity of situations. The study shows the potential of the described trend analysis as a predictive monitoring tool, as it provides an advantage over the traditional manual inspection of variables by detecting changes in water quality and giving early warnings.

Analysis and design of the ultraviolet warning optical system based on interference imaging

NASA Astrophysics Data System (ADS)

Wang, Wen-cong; Hu, Hui-jun; Jin, Dong-dong; Chu, Xin-bo; Shi, Yu-feng; Song, Juan; Liu, Jin-sheng; Xiao, Ting; Shao, Si-pei

2017-10-01

Ultraviolet warning technology is one of the important methods for missile warning. It provides a very effective way to detect the target for missile approaching alarm. With the development of modern technology, especially the development of information technology at high speed, the ultraviolet early warning system plays an increasingly important role. Compared to infrared warning, the ultraviolet warning has high efficiency and low false alarm rate. In the modern warfare, how to detect the threats earlier, prevent and reduce the attack of precision-guided missile has become a new challenge of missile warning technology. Because the ultraviolet warning technology has high environmental adaptability, the low false alarm rate, small volume and other advantages, in the military field applications it has been developed rapidly. For the ultraviolet warning system, the optimal working waveband is 250 nm 280 nm (Solar Blind UV) due to the strong absorption of ozone layer. According to current application demands for solar blind ultraviolet detection and warning, this paper proposes ultraviolet warning optical system based on interference imaging, which covers solar blind ultraviolet (250nm-280nm) and dual field. This structure includes a primary optical system, an ultraviolet reflector array, an ultraviolet imaging system and an ultraviolet interference imaging system. It makes use of an ultraviolet beam-splitter to achieve the separation of two optical systems. According to the detector and the corresponding application needs of two visual field of the optical system, the calculation and optical system design were completed. After the design, the MTF of the two optical system is more than 0.8@39lp/mm.A single pixel energy concentration is greater than 80%.

Demonstration of the Cascadia G‐FAST geodetic earthquake early warning system for the Nisqually, Washington, earthquake

USGS Publications Warehouse

Crowell, Brendan; Schmidt, David; Bodin, Paul; Vidale, John; Gomberg, Joan S.; Hartog, Renate; Kress, Victor; Melbourne, Tim; Santillian, Marcelo; Minson, Sarah E.; Jamison, Dylan

2016-01-01

A prototype earthquake early warning (EEW) system is currently in development in the Pacific Northwest. We have taken a two‐stage approach to EEW: (1) detection and initial characterization using strong‐motion data with the Earthquake Alarm Systems (ElarmS) seismic early warning package and (2) the triggering of geodetic modeling modules using Global Navigation Satellite Systems data that help provide robust estimates of large‐magnitude earthquakes. In this article we demonstrate the performance of the latter, the Geodetic First Approximation of Size and Time (G‐FAST) geodetic early warning system, using simulated displacements for the 2001Mw 6.8 Nisqually earthquake. We test the timing and performance of the two G‐FAST source characterization modules, peak ground displacement scaling, and Centroid Moment Tensor‐driven finite‐fault‐slip modeling under ideal, latent, noisy, and incomplete data conditions. We show good agreement between source parameters computed by G‐FAST with previously published and postprocessed seismic and geodetic results for all test cases and modeling modules, and we discuss the challenges with integration into the U.S. Geological Survey’s ShakeAlert EEW system.

Neural correlates of cigarette health warning avoidance among smokers.

PubMed

Stothart, George; Maynard, Olivia; Lavis, Rosie; Munafò, Marcus

2016-04-01

Eye-tracking technology has indicated that daily smokers actively avoid pictorial cigarette package health warnings. Avoidance may be due to a pre-cognitive perceptual bias or a higher order cognitive bias, such as reduced emotional processing. Using electroencephalography (EEG), this study aimed to identify the temporal point at which smokers' responses to health warnings begin to differ. Non-smokers (n=20) and daily smokers (n=20) viewed pictorial cigarette package health warnings and neutral control stimuli. These elicited Event Related Potentials reflecting early perceptual processing (visual P1), pre-attentive change detection (visual Mismatch Negativity), selective attentional orientation (P3) and a measure of emotional processing, the Late Positive Potential (LPP). There was no evidence for a difference in P1 responses between smokers and non-smokers. There was no difference in vMMN and P3 amplitude but some evidence for a delay in vMMN latency amongst smokers. There was strong evidence for delayed and reduced LPP to health warning stimuli amongst smokers compared to non-smokers. We find no evidence for an early perceptual bias in smokers' visual perception of health warnings but strong evidence that smokers are less sensitive to the emotional content of cigarette health warnings. Future health warning development should focus on increasing the emotional salience of pictorial health warning content amongst smokers. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

DISTANT EARLY WARNING SYSTEM for Tsunamis - A wide-area and multi-hazard approach

NASA Astrophysics Data System (ADS)

Hammitzsch, Martin; Lendholt, Matthias; Wächter, Joachim

2010-05-01

The DEWS (Distant Early Warning System) [1] project, funded under the 6th Framework Programme of the European Union, has the objective to create a new generation of interoperable early warning systems based on an open sensor platform. This platform integrates OGC [2] SWE [3] compliant sensor systems for the rapid detection of hazardous events, like earthquakes, sea level anomalies, ocean floor occurrences, and ground displacements in the case of tsunami early warning. Based on the upstream information flow DEWS focuses on the improvement of downstream capacities of warning centres especially by improving information logistics for effective and targeted warning message aggregation for a multilingual environment. Multiple telecommunication channels will be used for the dissemination of warning messages. Wherever possible, existing standards have been integrated. The Command and Control User Interface (CCUI), a rich client application based on Eclipse RCP (Rich Client Platform) [4] and the open source GIS uDig [5], integrates various OGC services. Using WMS (Web Map Service) [6] and WFS (Web Feature Service) [7] spatial data are utilized to depict the situation picture and to integrate a simulation system via WPS (Web Processing Service) [8] to identify affected areas. Warning messages are compiled and transmitted in the OASIS [9] CAP (Common Alerting Protocol) [10] standard together with addressing information defined via EDXL-DE (Emergency Data Exchange Language - Distribution Element) [11]. Internal interfaces are realized with SOAP [12] web services. Based on results of GITEWS [13] - in particular the GITEWS Tsunami Service Bus [14] - the DEWS approach provides an implementation for tsunami early warning systems but other geological paradigms are going to follow, e.g. volcanic eruptions or landslides. Therefore in future also multi-hazard functionality is conceivable. The specific software architecture of DEWS makes it possible to dock varying sensors to the system and to extend the CCUI with hazard specific functionality. The presentation covers the DEWS project, the system architecture and the CCUI in conjunction with details of information logistics. The DEWS Wide Area Centre connecting national centres to allow the international communication and warning exchange is presented also. REFERENCES: [1] DEWS, www.dews-online.org [2] OGC, www.opengeospatial.org [3] SWE, www.opengeospatial.org/projects/groups/sensorweb [4] Eclipse RCP, www.eclipse.org/home/categories/rcp.php [5] uDig, udig.refractions.net [6] WMS, www.opengeospatial.org/standards/wms [7] WFS, www.opengeospatial.org/standards/wfs [8] WPS, www.opengeospatial.org/standards/wps [9] OASIS, www.oasis-open.org [10] CAP, www.oasis-open.org/specs/#capv1.1 [11] EDXL-DE, www.oasis-open.org/specs/#edxlde-v1.0 [12] SOAP, www.w3.org/TR/soap [13] GITEWS (German Indonesian Tsunami Early Warning System) is a project of the German Federal Government to aid the recon¬struction of the tsunami-prone Indian Ocean region, www.gitews.org [14] The Tsunami Service Bus is the GITEWS sensor system integration platform offering standardised services for the detection and monitoring of tsunamis

Fire Won't Wait--Plan Your Escape!

ERIC Educational Resources Information Center

PTA Today, 1991

1991-01-01

Discusses the importance of home fire escape drills, detailing fire safety plans. Early detection and warning (smoke detectors) coupled with well-rehearsed escape plans help prevent serious injury. Children need to be taught about fire safety beginning at a very early age. (SM)

An analysis of an early-warning system to reduce abortions in dairy cattle in Denmark incorporating both financial and epidemiologic aspects.

PubMed

Carpenter, Tim E; Chrièl, Mariann; Greiner, Matthias

2007-01-16

Emergency preparedness relies on the ability to detect patterns in rare incidents in an early stage of an outbreak in order to implement relevant actions. Early warning of an abortion storm as a result of infection with a notifiable disease, e.g. brucellosis, bovine viral diarrhea (BVD) or infectious bovine rhinotracheitis (IBR), is a significant surveillance tool. This study used data from 507 large Danish dairy herds. A modified two-stage method for detecting an unusual increase in the abortion incidence was applied to the data. An alarm was considered true if an abortion were detected in the month following the alarm month, otherwise false. The total number of abortions that could potentially be avoided if effective action were taken ranged from 769 (22.9%) to 10 (0.3%), as the number of abortions required to set the alarm increased from 1 to 6. The vast majority of abortions could, however, not be predicted, much less prevented, given this early-warning system. The false to true alarm ratio was reduced when the number of abortions that set the alarm increased. The financial scenarios evaluated demonstrated that the value of an abortion, the cost of responding to an alarm and the efficiency of the actions are important for decision making when reporting an alarm. The presented model can readily be extended to other disease problems and multiple-time periods.

Automated online optical biosensing system for continuous real-time determination of microcystin-LR with high sensitivity and specificity: early warning for cyanotoxin risk in drinking water sources.

PubMed

Shi, Han-Chang; Song, Bao-Dong; Long, Feng; Zhou, Xiao-Hong; He, Miao; Lv, Qing; Yang, Hai-Yang

2013-05-07

The accelerated eutrophication of surface water sources and climate change have led to an annual occurrence of cyanobacterial blooms in many drinking water resources. To minimize the health risks to the public, cyanotoxin detection methods that are rapid, sensitive, real time, and high frequency must be established. In this study, an innovative automated online optical biosensing system (AOBS) was developed for the rapid detection and early warning of microcystin-LR (MC-LR), one of the most toxic cyanotoxins and most frequently detected in environmental water. In this system, the capturing molecular MC-LR-ovalbumin (MC-LR-OVA) was covalently immobilized onto a biochip surface. By an indirect competitive detection mode, samples containing different concentrations of MC-LR were premixed with a certain concentration of fluorescence-labeled anti-MC-LR-mAb, which binds to MC-LR with high specificity. Then, the sample mixture was pumped onto the biochip surface, and a higher concentration of MC-LR led to less fluorescence-labeled antibody bound onto the biochip surface and thus to lower fluorescence signal. The quantification of MC-LR ranges from 0.2 to 4 μg/L, with a detection limit determined as 0.09 μg/L. The high specificity and selectivity of the sensor were evaluated in terms of its response to a number of potentially interfering cyanotoxins. Potential interference of the environmental sample matrix was assessed by spiked samples, and the recovery of MC-LR ranged from 90 to 120% with relative standard deviation values <8%. The immunoassay performance of the AOBS was validated with respect to that of conventional high-performance liquid chromatography, and the correlation between methods agreed well (R(2) = 0.9762). This system has successfully been applied to long-term, continuous determination and early warning for MC-LR in Lake Tai from June 2011 to May 2012. Thus, the AOBS paves the way for a vital routine online analysis that satisfies the high demand for ensuring the safety of drinking water sources. The AOBS can also serve as early warning system for accidental or intentional water pollution.

Using natural archives to detect climate and environmental tipping points in the Earth System

NASA Astrophysics Data System (ADS)

Thomas, Zoë A.

2016-11-01

'Tipping points' in the Earth system are characterised by a nonlinear response to gradual forcing, and may have severe and wide-ranging impacts. Many abrupt events result from simple underlying system dynamics termed 'critical transitions' or 'bifurcations'. One of the best ways to identify and potentially predict threshold behaviour in the climate system is through analysis of natural ('palaeo') archives. Specifically, on the approach to a tipping point, early warning signals can be detected as characteristic fluctuations in a time series as a system loses stability. Testing whether these early warning signals can be detected in highly complex real systems is a key challenge, since much work is either theoretical or only tested with simple models. This is particularly problematic in palaeoclimate and palaeoenvironmental records with low resolution, non-equidistant data, which can limit accurate analysis. Here, a range of different datasets are examined to explore generic rules that can be used to detect such dramatic events. A number of key criteria are identified to be necessary for the reliable identification of early warning signals in natural archives, most crucially, the need for a low-noise record of sufficient data length, resolution and accuracy. A deeper understanding of the underlying system dynamics is required to inform the development of more robust system-specific indicators, or to indicate the temporal resolution required, given a known forcing. This review demonstrates that time series precursors from natural archives provide a powerful means of forewarning tipping points within the Earth System.

Solar Energetic Particle Warnings from a Coronagraph

NASA Technical Reports Server (NTRS)

St Cyr, O. C.; Posner, A.; Burkepile, J. T.

2017-01-01

We report here the concept of using near-real time observations from a coronagraph to provide early warning of a fast coronal mass ejection (CME) and the possible onset of a solar energetic particle (SEP) event. The 1 January 2016, fast CME, and its associated SEP event are cited as an example. The CME was detected by the ground-based K-Cor coronagraph at Mauna Loa Solar Observatory and by the SOHO Large Angle and Spectrometric Coronagraph. The near-real-time availability of the high-cadence K-Cor observations in the low corona leads to an obvious question: Why has no one attempted to use a coronagraph as an early warning device for SEP events? The answer is that the low image cadence and the long latency of existing spaceborne coronagraphs make them valid for archival studies but typically unsuitable for near-real-time forecasting. The January 2016 event provided favorable CME viewing geometry and demonstrated that the primary component of a prototype ground-based system for SEP warnings is available several hours on most days. We discuss how a conceptual CME-based warning system relates to other techniques, including an estimate of the relative SEP warning times, and how such a system might be realized.

Highlight on Supernova Early Warning at Daya Bay

NASA Astrophysics Data System (ADS)

Wei, Hanyu

Providing an early warning of supernova burst neutrinos is of importance in studying both supernova dynamics and neutrino physics. The Daya Bay Reactor Neutrino Experiment, with a unique feature of multiple liquid scintillator detectors, is sensitive to the full energy spectrum of supernova burst electron-antineutrinos. By utilizing 8 Antineutrino Detectors (ADs) in the three different experimental halls which are about 1 km's apart from each other, we obtain a powerful and prompt rejection of muon spallation background than single-detector experiments with the same target volume. A dedicated trigger system embedded in the data acquisition system has been installed to allow the detection of a coincidence of neutrino signals of all ADs via an inverse beta-decay (IBD) within a 10-second window, thus providing a robust early warning of a supernova occurrence within the Milky Way. An 8-AD associated supernova trigger table has been established theoretically to tabulate the 8-AD event counts' coincidence vs. the trigger rate. As a result, a golden trigger threshold, i.e. with a false alarm rate < 1/3-months, can be set as low as 6 candidates among the 8 detectors, leading to a 100% detection probability for all 1987A type supernova bursts at the distance to the Milky Way center and a 96% detection probability to those at the edge of the Milky Way.

Real-Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

NASA Astrophysics Data System (ADS)

Kodera, Yuki

2018-01-01

Large earthquakes with long rupture durations emit P wave energy throughout the rupture period. Incorporating late-onset P waves into earthquake early warning (EEW) algorithms could contribute to robust predictions of strong ground motion. Here I describe a technique to detect in real time P waves from growing ruptures to improve the timeliness of an EEW algorithm based on seismic wavefield estimation. The proposed P wave detector, which employs a simple polarization analysis, successfully detected P waves from strong motion generation areas of the 2011 Mw 9.0 Tohoku-oki earthquake rupture. An analysis using 23 large (M ≥ 7) events from Japan confirmed that seismic intensity predictions based on the P wave detector significantly increased lead times without appreciably decreasing the prediction accuracy. P waves from growing ruptures, being one of the fastest carriers of information on ongoing rupture development, have the potential to improve the performance of EEW systems.

Space geodetic tools provide early warnings for earthquakes and volcanic eruptions

NASA Astrophysics Data System (ADS)

Aoki, Yosuke

2017-04-01

Development of space geodetic techniques such as Global Navigation Satellite System and Synthetic Aperture Radar in last few decades allows us to monitor deformation of Earth's surface in unprecedented spatial and temporal resolution. These observations, combined with fast data transmission and quick data processing, enable us to quickly detect and locate earthquakes and volcanic eruptions and assess potential hazards such as strong earthquake shaking, tsunamis, and volcanic eruptions. These techniques thus are key parts of early warning systems, help identify some hazards before a cataclysmic event, and improve the response to the consequent damage.

Forecasting infectious disease emergence subject to seasonal forcing.

PubMed

Miller, Paige B; O'Dea, Eamon B; Rohani, Pejman; Drake, John M

2017-09-06

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models. We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic. Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly. Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

Enhanced early warning system impact on nursing practice: A phenomenological study.

PubMed

Burns, Kathleen A; Reber, Tracey; Theodore, Karen; Welch, Brenda; Roy, Debra; Siedlecki, Sandra L

2018-05-01

To determine how an enhanced early warning system has an impact on nursing practice. Early warning systems score physiologic measures and alert nurses to subtle changes in patient condition. Critics of early warning systems have expressed concern that nurses would rely on a score rather than assessment skills and critical thinking to determine the need for intervention. Enhancing early warning systems with innovative technology is still in its infancy, so the impact of an enhanced early warning system on nursing behaviours or practice has not yet been studied. Phenomenological design. Scripted, semistructured interviews were conducted in September 2015 with 25 medical/surgical nurses who used the enhanced early warning system. Data were analysed using thematic analysis techniques (coding and bracketing). Emerging themes were examined for relationships and a model describing the enhanced early warning system experience was developed. Nurses identified awareness leading to investigation and ease of prioritization as the enhanced early warning system's most important impact on their nursing practice. There was also an impact on organizational culture, with nurses reporting improved communication, increased collaboration, increased accountability and proactive responses to early changes in patient condition. Rather than hinder critical thinking, as many early warning systems' critics claim, nurses in this study found that the enhanced early warning system increased their awareness of changes in a patient's condition, resulting in earlier response and reassessment times. It also had an impact on the organization by improving communication and collaboration and supporting a culture of proactive rather than reactive response to early signs of deterioration. © 2017 John Wiley & Sons Ltd.

Towards an Automated Acoustic Detection System for Free Ranging Elephants.

PubMed

Zeppelzauer, Matthias; Hensman, Sean; Stoeger, Angela S

The human-elephant conflict is one of the most serious conservation problems in Asia and Africa today. The involuntary confrontation of humans and elephants claims the lives of many animals and humans every year. A promising approach to alleviate this conflict is the development of an acoustic early warning system. Such a system requires the robust automated detection of elephant vocalizations under unconstrained field conditions. Today, no system exists that fulfills these requirements. In this paper, we present a method for the automated detection of elephant vocalizations that is robust to the diverse noise sources present in the field. We evaluate the method on a dataset recorded under natural field conditions to simulate a real-world scenario. The proposed method outperformed existing approaches and robustly and accurately detected elephants. It thus can form the basis for a future automated early warning system for elephants. Furthermore, the method may be a useful tool for scientists in bioacoustics for the study of wildlife recordings.

Patient attitudes towards remote continuous vital signs monitoring on general surgery wards: An interview study.

PubMed

Downey, C L; Brown, J M; Jayne, D G; Randell, R

2018-06-01

Vital signs monitoring is used to identify deteriorating patients in hospital. The most common tool for vital signs monitoring is an early warning score, although emerging technologies allow for remote, continuous patient monitoring. A number of reviews have examined the impact of continuous monitoring on patient outcomes, but little is known about the patient experience. This study aims to discover what patients think of monitoring in hospital, with a particular emphasis on intermittent early warning scores versus remote continuous monitoring, in order to inform future implementations of continuous monitoring technology. Semi-structured interviews were undertaken with 12 surgical inpatients as part of a study testing a remote continuous monitoring device. All patients were monitored with both an early warning score and the new device. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis. Patients can see the value in remote, continuous monitoring, particularly overnight. However, patients appreciate the face-to-face aspect of early warning score monitoring as it allows for reassurance, social interaction, and gives them further opportunity to ask questions about their medical care. Early warning score systems are widely used to facilitate detection of the deteriorating patient. Continuous monitoring technologies may provide added reassurance. However, patients value personal contact with their healthcare professionals and remote monitoring should not replace this. We suggest that remote monitoring is best introduced in a phased manner, and initially as an adjunct to usual care, with careful consideration of the patient experience throughout. Copyright © 2018 Elsevier B.V. All rights reserved.

Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness

PubMed Central

Lenton, T. M.; Livina, V. N.; Dakos, V.; Van Nes, E. H.; Scheffer, M.

2012-01-01

We address whether robust early warning signals can, in principle, be provided before a climate tipping point is reached, focusing on methods that seek to detect critical slowing down as a precursor of bifurcation. As a test bed, six previously analysed datasets are reconsidered, three palaeoclimate records approaching abrupt transitions at the end of the last ice age and three models of varying complexity forced through a collapse of the Atlantic thermohaline circulation. Approaches based on examining the lag-1 autocorrelation function or on detrended fluctuation analysis are applied together and compared. The effects of aggregating the data, detrending method, sliding window length and filtering bandwidth are examined. Robust indicators of critical slowing down are found prior to the abrupt warming event at the end of the Younger Dryas, but the indicators are less clear prior to the Bølling-Allerød warming, or glacial termination in Antarctica. Early warnings of thermohaline circulation collapse can be masked by inter-annual variability driven by atmospheric dynamics. However, rapidly decaying modes can be successfully filtered out by using a long bandwidth or by aggregating data. The two methods have complementary strengths and weaknesses and we recommend applying them together to improve the robustness of early warnings. PMID:22291229

An early warning indicator for atmospheric blocking events using transfer operators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tantet, Alexis, E-mail: a.j.j.tantet@uu.nl; Burgt, Fiona R. van der; Dijkstra, Henk A.

The existence of persistent midlatitude atmospheric flow regimes with time-scales larger than 5–10 days and indications of preferred transitions between them motivates to develop early warning indicators for such regime transitions. In this paper, we use a hemispheric barotropic model together with estimates of transfer operators on a reduced phase space to develop an early warning indicator of the zonal to blocked flow transition in this model. It is shown that the spectrum of the transfer operators can be used to study the slow dynamics of the flow as well as the non-Markovian character of the reduction. The slowest motionsmore » are thereby found to have time scales of three to six weeks and to be associated with meta-stable regimes (and their transitions) which can be detected as almost-invariant sets of the transfer operator. From the energy budget of the model, we are able to explain the meta-stability of the regimes and the existence of preferred transition paths. Even though the model is highly simplified, the skill of the early warning indicator is promising, suggesting that the transfer operator approach can be used in parallel to an operational deterministic model for stochastic prediction or to assess forecast uncertainty.« less

[Early detection on the onset of scarlet fever epidemics in Beijing, using the Cumulative Sum].

PubMed

Li, Jing; Yang, Peng; Wu, Shuang-sheng; Wang, Xiao-li; Liu, Shuang; Wang, Quan-yi

2013-05-01

Based on data related to scarlet fever which was collected from the Disease Surveillance Information Reporting System in Beijing from 2005 to 2011, to explore the efficiency of Cumulative Sum (CUSUM) in detecting the onset of scarlet fever epidemics. Models as C1-MILD (C1), C2-MEDIUM (C2) and C3-ULTRA (C3) were used. Tools for evaluation as Youden's index and detection time were calculated to optimize the parameters and optimal model. Data on 2011 scarlet fever surveillance was used to verify the efficacy of these models. C1 (k = 0.5, H = 2σ), C2 (k = 0.7, H = 2σ), C3 (k = 1.1, H = 2σ) appeared to be the optimal parameters among these models. Youden's index of C1 was 83.0% and detection time being 0.64 weeks, Youden's index of C2 was 85.4% and detection time being 1.27 weeks, Youden's index of C1 was 85.1% and detection time being 1.36 weeks. Among the three early warning detection models, C1 had the highest efficacy. Three models all triggered the signals within 4 weeks after the onset of scarlet fever epidemics. The early warning detection model of CUSUM could be used to detect the onset of scarlet fever epidemics, with good efficacy.

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

PubMed

Jarvis, Stuart; Kovacs, Caroline; Briggs, Jim; Meredith, Paul; Schmidt, Paul E; Featherstone, Peter I; Prytherch, David R; Smith, Gary B

2015-08-01

Although the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. We truncated 36 published 'standard' EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve--AUROC) of each standard EWS and its truncated 'binary' equivalent. The binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. The performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

New early warning system for gravity-driven ruptures based on codetection of acoustic signal

NASA Astrophysics Data System (ADS)

Faillettaz, J.

2016-12-01

Gravity-driven rupture phenomena in natural media - e.g. landslide, rockfalls, snow or ice avalanches - represent an important class of natural hazards in mountainous regions. To protect the population against such events, a timely evacuation often constitutes the only effective way to secure the potentially endangered area. However, reliable prediction of imminence of such failure events remains challenging due to the nonlinear and complex nature of geological material failure hampered by inherent heterogeneity, unknown initial mechanical state, and complex load application (rainfall, temperature, etc.). Here, a simple method for real-time early warning that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. This new method capitalizes on codetection of elastic waves emanating from microcracks by multiple and spatially separated sensors. Event-codetection is considered as surrogate for large event size with more frequent codetected events (i.e., detected concurrently on more than one sensor) marking imminence of catastrophic failure. Simple numerical model based on a Fiber Bundle Model considering signal attenuation and hypothetical arrays of sensors confirms the early warning potential of codetection principles. Results suggest that although statistical properties of attenuated signal amplitude could lead to misleading results, monitoring the emergence of large events announcing impeding failure is possible even with attenuated signals depending on sensor network geometry and detection threshold. Preliminary application of the proposed method to acoustic emissions during failure of snow samples has confirmed the potential use of codetection as indicator for imminent failure at lab scale. The applicability of such simple and cheap early warning system is now investigated at a larger scale (hillslope). First results of such a pilot field experiment are presented and analysed.

Early warning system for financially distressed hospitals via data mining application.

PubMed

Koyuncugil, Ali Serhan; Ozgulbas, Nermin

2012-08-01

The aim of this study is to develop a Financial Early Warning System (FEWS) for hospitals by using data mining. A data mining method, Chi-Square Automatic Interaction Detector (CHAID) decision tree algorithm, was used in the study for financial profiling and developing FEWS. The study was conducted in Turkish Ministry of Health's public hospitals which were in financial distress and in need of urgent solutions for financial issues. 839 hospitals were covered and financial data of the year 2008 was obtained from Ministry of Health. As a result of the study, it was determined that 28 hospitals (3.34%) had good financial performance, and 811 hospitals (96.66%) had poor financial performance. According to FEWS, the covered hospitals were categorized into 11 different financial risk profiles, and it was found that 6 variables affected financial risk of hospitals. According to the profiles of hospitals in financial distress, one early warning signal was detected and financial road map was developed for risk mitigation.

Determination of early warning signs for photocatalytic degradation of titanium white oil paints by means of surface analysis

NASA Astrophysics Data System (ADS)

van Driel, B. A.; Wezendonk, T. A.; van den Berg, K. J.; Kooyman, P. J.; Gascon, J.; Dik, J.

2017-02-01

Titanium white (TiO2) has been widely used as a pigment in the 20th century. However, its most photocatalytic form (anatase) can cause severe degradation of the oil paint in which it is contained. UV light initiates TiO2-photocatalyzed processes in the paint film, degrading the oil binder into volatile components resulting in chalking of the paint. This will eventually lead to severe changes in the appearance of a painting. To date, limited examples of degraded works of art containing titanium white are known due to the relatively short existence of the paintings in question and the slow progress of the degradation process. However, UV light will inevitably cause degradation of paint in works of art containing photocatalytic titanium white. In this work, a method to detect early warning signs of photocatalytic degradation of unvarnished oil paint is proposed, using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Consequently, a four-stage degradation model was developed through in-depth study of TiO2-containing paint films in various stages of degradation. The XPS surface analysis proved very valuable for detecting early warning signs of paint degradation, whereas the AFM results provide additional confirmation and are in good agreement with bulk gloss reduction.

The Role of North American Aerospace Defense Command (NORAD) In Military Cyber Attack Warning

DTIC Science & Technology

2015-09-01

WARNING MISSIONS .....................................5  1.  Early North American Air Defense Warning ...................................5  2...BLANK xi LIST OF FIGURES Figure 1.   North American Distant Early Warning (DEW) Site. .......................................6  Figure 2.   Original... Early Warning (AEW) Aircraft .........................................11  Figure 7.   Headquarters NORAD and USNORTHCOM

A hazard-independent approach for the standardised multi-channel dissemination of warning messages

NASA Astrophysics Data System (ADS)

Esbri Palomares, M. A.; Hammitzsch, M.; Lendholt, M.

2012-04-01

The tsunami disaster affecting the Indian Ocean region on Christmas 2004 demonstrated very clearly the shortcomings in tsunami detection, public warning processes as well as intergovernmental warning message exchange in the Indian Ocean region. In that regard, early warning systems require that the dissemination of early warning messages has to be executed in way that ensures that the message delivery is timely; the message content is understandable, usable and accurate. To that end, diverse and multiple dissemination channels must be used to increase the chance of the messages reaching all affected persons in a hazard scenario. In addition to this, usage of internationally accepted standards for the warning dissemination such as the Common Alerting Protocol (CAP) and Emergency Data Exchange Language (EDXL) Distribution Element specified by the Organization for the Advancement of Structured Information Standards (OASIS) increase the interoperability among different warning systems enabling thus the concept of system-of-systems proposed by GEOSS. The project Distant Early Warning System (DEWS), co-funded by the European Commission under the 6th Framework Programme, aims at strengthening the early warning capacities by building an innovative generation of interoperable tsunami early warning systems based on the above mentioned concepts following a Service-oriented Architecture (SOA) approach. The project focuses on the downstream part of the hazard information processing where customized, user-tailored warning messages and alerts flow from the warning centre to the responsible authorities and/or the public with their different needs and responsibilities. The information logistics services within DEWS generate tailored EDXL-DE/CAP warning messages for each user that must receive the message according to their preferences, e.g., settings for language, interested areas, dissemination channels, etc.. However, the significant difference in the implementation and capabilities of different dissemination channels such as SMS, email and television, have bearing on the information processing required for delivery and consumption of a DEWS EDXL-DE/CAP message over each dissemination channel. These messages may include additional information in the form of maps, graphs, documents, sensor observations, etc. Therefore, the generated messages are pre-processed by channel adaptors in the information dissemination services converting it into a format that is suitable for end-to-end delivery over the dissemination channels without any semantic distortion. The approach followed by DEWS for disseminating warnings not only relies on traditional communication ways used by the already established early warnings such as the delivery of faxes and phone calls but takes into consideration the use of other broadly used communication channels such as SMS, email, narrowcast and broadcast television, instant messaging, Voice over IP, and radio. It also takes advantage of social media channels like RSS feeds, Facebook, Twitter, etc., enabling a multiplier effect, like in the case of radio and television, and thus allowing to create mash-ups by aggregating other sources of information to the original message. Finally, status information is also important in order to assess and understand whether the process of disseminating the warning to the message consumers has been successfully completed or the process failed at some point of the dissemination chain. To that end, CAP-based messages generated within the information dissemination services provide the semantics for those fields that are of interest within the context of reporting the warning dissemination status in DEWS.

Application of Collocated GPS and Seismic Sensors to Earthquake Monitoring and Early Warning

PubMed Central

Li, Xingxing; Zhang, Xiaohong; Guo, Bofeng

2013-01-01

We explore the use of collocated GPS and seismic sensors for earthquake monitoring and early warning. The GPS and seismic data collected during the 2011 Tohoku-Oki (Japan) and the 2010 El Mayor-Cucapah (Mexico) earthquakes are analyzed by using a tightly-coupled integration. The performance of the integrated results is validated by both time and frequency domain analysis. We detect the P-wave arrival and observe small-scale features of the movement from the integrated results and locate the epicenter. Meanwhile, permanent offsets are extracted from the integrated displacements highly accurately and used for reliable fault slip inversion and magnitude estimation. PMID:24284765

Development of communication networks and water quality early warning detection systems at drinking water utilities in the Ohio River Valley Basin.

PubMed

Schulte, J G; Vicory, A H

2005-01-01

Source water quality is of major concern to all drinking water utilities. The accidental introduction of contaminants to their source water is a constant threat to utilities withdrawing water from navigable or industrialized rivers. The events of 11 September, 2001 in the United States have heightened concern for drinking water utility security as their source water and finished water may be targets for terrorist acts. Efforts are underway in several parts of the United States to strengthen early warning capabilities. This paper will focus on those efforts in the Ohio River Valley Basin.

Earthquake Early Warning and Public Policy: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Goltz, J. D.; Bourque, L.; Tierney, K.; Riopelle, D.; Shoaf, K.; Seligson, H.; Flores, P.

2003-12-01

Development of an earthquake early warning capability and pilot project were objectives of TriNet, a 5-year (1997-2001) FEMA-funded project to develop a state-of-the-art digital seismic network in southern California. In parallel with research to assemble a protocol for rapid analysis of earthquake data and transmission of a signal by TriNet scientists and engineers, the public policy, communication and educational issues inherent in implementation of an earthquake early warning system were addressed by TriNet's outreach component. These studies included: 1) a survey that identified potential users of an earthquake early warning system and how an earthquake early warning might be used in responding to an event, 2) a review of warning systems and communication issues associated with other natural hazards and how lessons learned might be applied to an alerting system for earthquakes, 3) an analysis of organization, management and public policy issues that must be addressed if a broad-based warning system is to be developed and 4) a plan to provide earthquake early warnings to a small number of organizations in southern California as an experimental prototype. These studies provided needed insights into the social and cultural environment in which this new technology will be introduced, an environment with opportunities to enhance our response capabilities but also an environment with significant barriers to overcome to achieve a system that can be sustained and supported. In this presentation we will address the main public policy issues that were subjects of analysis in these studies. They include a discussion of the possible division of functions among organizations likely to be the principle partners in the management of an earthquake early warning system. Drawing on lessons learned from warning systems for other hazards, we will review the potential impacts of false alarms and missed events on warning system credibility, the acceptability of fully automated warning systems and equity issues associated with possible differential access to warnings. Finally, we will review the status of legal authorities and liabilities faced by organizations that assume various warning system roles and possible approaches to setting up a pilot project to introduce early warning. Our presentation will suggest that introducing an early warning system requires multi-disciplinary and multi-agency cooperation and thoughtful discussion among organizations likely to be providers and participants in an early warning system. Recalling our experience with earthquake prediction, we will look at early warning as a promising but unproven technology and recommend moving forward with caution and patience.

Cyanobacteria Assessment Network (CyAN)

EPA Pesticide Factsheets

CyAN is a multi-agency project among the National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), US Geological Survey (USGS), and EPA to develop an early warning indicator system to detect algal blooms.

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William W.; Gasser, Gerald

2013-01-01

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Development of a GNSS-Enhanced Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Bawden, G. W.; Melbourne, T. I.; Bock, Y.; Song, Y. T.; Komjathy, A.

2015-12-01

The past decade has witnessed a terrible loss of life and economic disruption caused by large earthquakes and resultant tsunamis impacting coastal communities and infrastructure across the Indo-Pacific region. NASA has funded the early development of a prototype real-time Global Navigation Satellite System (RT-GNSS) based rapid earthquake and tsunami early warning (GNSS-TEW) system that may be used to enhance seismic tsunami early warning systems for large earthquakes. This prototype GNSS-TEW system geodetically estimates fault parameters (earthquake magnitude, location, strike, dip, and slip magnitude/direction on a gridded fault plane both along strike and at depth) and tsunami source parameters (seafloor displacement, tsunami energy scale, and 3D tsunami initials) within minutes after the mainshock based on dynamic numerical inversions/regressions of the real-time measured displacements within a spatially distributed real-time GNSS network(s) spanning the epicentral region. It is also possible to measure fluctuations in the ionosphere's total electron content (TEC) in the RT-GNSS data caused by the pressure wave from the tsunami. This TEC approach can detect if a tsunami has been triggered by an earthquake, track its waves as they propagate through the oceanic basins, and provide upwards of 45 minutes early warning. These combined real-time geodetic approaches will very quickly address a number of important questions in the immediate minutes following a major earthquake: How big was the earthquake and what are its fault parameters? Could the earthquake have produced a tsunami and was a tsunami generated?

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

PubMed

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Study on Early-Warning System of Cotton Production in Hebei Province

NASA Astrophysics Data System (ADS)

Zhang, Runqing; Ma, Teng

Cotton production plays an important role in Hebei. It straightly influences cotton farmers’ life, agricultural production and national economic development as well. In recent years, due to cotton production frequently fluctuating, two situations, “difficult selling cotton” and “difficult buying cotton” have alternately occurred, and brought disadvantages to producers, businesses and national finance. Therefore, it is very crucial to research the early warning of cotton production for solving the problem of cotton production’s frequent fluctuation and ensuring the cotton industry’s sustainable development. This paper founds a signal lamp model of early warning through employing time-difference correlation analysis method to select early-warning indicators and statistical analysis method associated with empirical analysis to determine early-warning limits. Finally, it not only obtained warning conditions of cotton production from 1993 to 2006 and forecast 2007’s condition, but also put forward corresponding countermeasures to prevent cotton production from fluctuating. Furthermore, an early-warning software of cotton production is completed through computer programming on the basis of the early warning model above.

Flood Monitoring and Early Warning System Using Ultrasonic Sensor

NASA Astrophysics Data System (ADS)

Natividad, J. G.; Mendez, J. M.

2018-03-01

The purpose of this study is to develop a real-time flood monitoring and early warning system in the northern portion of the province of Isabela, particularly the municipalities near Cagayan River. Ultrasonic sensing techniques have become mature and are widely used in the various fields of engineering and basic science. One of advantage of ultrasonic sensing is its outstanding capability to probe inside objective non-destructively because ultrasound can propagate through any kinds of media including solids, liquids and gases. This study focuses only on the water level detection and early warning system (via website and/or SMS) that alerts concern agencies and individuals for a potential flood event. Furthermore, inquiry system is also included in this study to become more interactive wherein individuals in the community could inquire the actual water level and status of the desired area or location affected by flood thru SMS keyword. The study aims in helping citizens to be prepared and knowledgeable whenever there is a flood. The novelty of this work falls under the utilization of the Arduino, ultrasonic sensors, GSM module, web-monitoring and SMS early warning system in helping stakeholders to mitigate casualties related to flood. The paper envisions helping flood-prone areas which are common in the Philippines particularly to the local communities in the province. Indeed, it is relevant and important as per needs for safety and welfare of the community.

Use of cyanopigment determination as an indicator of cyanotoxins in drinking water.

PubMed

Schmidt, Wido; Petzoldt, Heike; Bornmann, Katrin; Imhof, Lutz; Moldaenke, Christian

2009-01-01

The indicator function of the fluorescence signals of the cyanopigments phycocyanin and phycoerythrin as early warning parameters against the microcystins in drinking water was investigated by lab- and pilot-scale studies. The early warning function of the fluorescence signals was examined with regard to the signals' real-time character, their sensitivity and the behaviour of the cyanopigments in different treatment stages in comparison to microcystins. Fluorescence measurements confirmed the real-time character, since they can be carried out on-site without the pre-concentration of pigments. The limit of detection of phycoerythrin is determined at 0.7 microg/L and of phycocyanin at 5.3 microg/L respectively. If the pigment/microcystin ratio is known and calculated to be higher than 1, very low microcystin concentrations can be estimated by the fluorescence signals. The compared behaviour of both pigments and selected microcystins (MC-LR and MC-RR) during water treatment shows that pigments have an early warning function against microcystins in conventional treatment stages using pre-oxidation with permanganate, powdered-activated carbon and chlorination. In contrast, cyanopigments do not have an early warning function if chlorine dioxide is used as a pre-oxidant or final disinfection agent. In order to use pigment control measurements in drinking water treatment the initial pigment/toxin ratio of the raw water must be known.

Spatial early warning signals in a lake manipulation

USGS Publications Warehouse

Butitta, Vince L.; Carpenter, Stephen R.; Loken, Luke; Pace, Michael L.; Stanley, Emily H.

2017-01-01

Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.

A real-time cabled observatory on the Cascadia subduction zone

NASA Astrophysics Data System (ADS)

Vidale, J. E.; Delaney, J. R.; Toomey, D. R.; Bodin, P.; Roland, E. C.; Wilcock, W. S. D.; Houston, H.; Schmidt, D. A.; Allen, R. M.

2015-12-01

Subduction zones are replete with mystery and rife with hazard. Along most of the Pacific Northwest margin, the traditional methods of monitoring offshore geophysical activity use onshore sensors or involve conducting infrequent oceanographic expeditions. This results in a limited capacity for detecting and monitoring subduction processes offshore. We propose that the next step in geophysical observations of Cascadia should include real-time data delivered by a seafloor cable with seismic, geodetic, and pressure-sensing instruments. Along the Cascadia subduction zone, we need to monitor deformation, earthquakes, and fluid fluxes on short time scales. High-quality long-term time series are needed to establish baseline observations and evaluate secular changes in the subduction environment. Currently we lack a basic knowledge of the plate convergence rate, direction and its variations along strike and of how convergence is accommodated across the plate boundary. We also would like to seek cycles of microseismicity, how far locking extends up-dip, and the transient processes (i.e., fluid pulsing, tremor, and slow slip) that occur near the trench. For reducing risk to society, real-time monitoring has great benefit for immediate and accurate assessment through earthquake early warning systems. Specifically, the improvement to early warning would be in assessing the location, geometry, and progression of ongoing faulting and obtaining an accurate tsunami warning, as well as simply speeding up the early warning. It would also be valuable to detect strain transients and map the locked portion of the megathrust, and detect changes in locking over the earthquake cycle. Development of the US portion of a real-time cabled seismic and geodetic observatory should build upon the Ocean Observatories Initiative's cabled array, which was recently completed and is currently delivering continuous seismic and pressure data from the seafloor. Its implementation would require substantial initial and ongoing investments from federal and state governments, private partners and the academic community but would constitute a critical resource in mitigating the hazard both through improved earthquake and tsunami warning and an enhanced scientific understanding of subduction processes in Cascadia.

Implementing Obstetric Early Warning Systems.

PubMed

Friedman, Alexander M; Campbell, Mary L; Kline, Carolyn R; Wiesner, Suzanne; D'Alton, Mary E; Shields, Laurence E

2018-04-01

Severe maternal morbidity and mortality are often preventable and obstetric early warning systems that alert care providers of potential impending critical illness may improve maternal safety. While literature on outcomes and test characteristics of maternal early warning systems is evolving, there is limited guidance on implementation. Given current interest in early warning systems and their potential role in care, the 2017 Society for Maternal-Fetal Medicine (SMFM) Annual Meeting dedicated a session to exploring early warning implementation across a wide range of hospital settings. This manuscript reports on key points from this session. While implementation experiences varied based on factors specific to individual sites, common themes relevant to all hospitals presenting were identified. Successful implementation of early warnings systems requires administrative and leadership support, dedication of resources, improved coordination between nurses, providers, and ancillary staff, optimization of information technology, effective education, evaluation of and change in hospital culture and practices, and support in provider decision-making. Evolving data on outcomes on early warning systems suggest that maternal risk may be reduced. To effectively reduce maternal, risk early warning systems that capture deterioration from a broad range of conditions may be required in addition to bundles tailored to specific conditions such as hemorrhage, thromboembolism, and hypertension.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG.

PubMed

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-03-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver's brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety.

Knowledge of stroke risk factors and early warning signs of stroke among students enrolled in allied health programs: a pilot study.

PubMed

Milner, Abby; Lewis, William J; Ellis, Charles

2008-01-01

The inclusion of stroke education modules early in medical school curricula has resulted in improved stroke knowledge in graduate physicians. The success of these programs suggests that allied health professions programs should also consider strategies to improve stroke knowledge in students preparing for allied health careers that also require knowledge of stroke risk factors and early warning signs. Currently, little is known about stroke knowledge in students enrolled in allied health professions programs. 208 first- and second-year students enrolled in allied health programs completed a survey of stroke risk factors and early warning signs of stroke. Risk factor knowledge - 99% identified smoking as a risk factor; 67% identified diabetes; 93% identified high cholesterol; 89% identified age; and 92% identified physical inactivity. Less than 50% of the students identified all 5 risk factors. There were no differences between first- and second-year students in risk factor knowledge. Early warning signs and first response knowledge - 89% recognized sudden confusion or trouble speaking; 94% recognized sudden facial, arm, or leg weakness; 65% recognized sudden vision loss; 82% recognized sudden trouble walking; and 73% recognized sudden headache as early warning signs of stroke. Eighty-one percent recognized calling 9-1-1 as the appropriate first action. However, only 25% recognized all five early warning signs and only 20% recognized all five early warning signs and would call 9-1-1 as the first action. There were differences between first- and second-year students in recognizing 3 of 5 early warning signs and appropriate first action to call 9-1-1. Most students recognized individual stroke risk factors and early warning signs but few recognized multiple risk factors and early warning signs of stroke.

37. View of detection radar environmental display (DRED) console for ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

37. View of detection radar environmental display (DRED) console for middle DR 2 (structure no. 736) antenna, located in MWOC facility. - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Detecting spatial regimes in ecosystems

USGS Publications Warehouse

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

A new type of tri-axial accelerometers with high dynamic range MEMS for earthquake early warning

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Chen, Yang; Chen, Quansheng; Yang, Jiansi; Wang, Hongti; Zhu, Xiaoyi; Xu, Zhiqiang; Zheng, Yu

2017-03-01

Earthquake Early Warning System (EEWS) has shown its efficiency for earthquake damage mitigation. As the progress of low-cost Micro Electro Mechanical System (MEMS), many types of MEMS-based accelerometers have been developed and widely used in deploying large-scale, dense seismic networks for EEWS. However, the noise performance of these commercially available MEMS is still insufficient for weak seismic signals, leading to the large scatter of early-warning parameters estimation. In this study, we developed a new type of tri-axial accelerometer based on high dynamic range MEMS with low noise level using for EEWS. It is a MEMS-integrated data logger with built-in seismological processing. The device is built on a custom-tailored Linux 2.6.27 operating system and the method for automatic detecting seismic events is STA/LTA algorithms. When a seismic event is detected, peak ground parameters of all data components will be calculated at an interval of 1 s, and τc-Pd values will be evaluated using the initial 3 s of P wave. These values will then be organized as a trigger packet actively sent to the processing center for event combining detection. The output data of all three components are calibrated to sensitivity 500 counts/cm/s2. Several tests and a real field test deployment were performed to obtain the performances of this device. The results show that the dynamic range can reach 98 dB for the vertical component and 99 dB for the horizontal components, and majority of bias temperature coefficients are lower than 200 μg/°C. In addition, the results of event detection and real field deployment have shown its capabilities for EEWS and rapid intensity reporting.

Design and internal validation of an obstetric early warning score: secondary analysis of the Intensive Care National Audit and Research Centre Case Mix Programme database.

PubMed

Carle, C; Alexander, P; Columb, M; Johal, J

2013-04-01

We designed and internally validated an aggregate weighted early warning scoring system specific to the obstetric population that has the potential for use in the ward environment. Direct obstetric admissions from the Intensive Care National Audit and Research Centre's Case Mix Programme Database were randomly allocated to model development (n = 2240) or validation (n = 2200) sets. Physiological variables collected during the first 24 h of critical care admission were analysed. Logistic regression analysis for mortality in the model development set was initially used to create a statistically based early warning score. The statistical score was then modified to create a clinically acceptable early warning score. Important features of this clinical obstetric early warning score are that the variables are weighted according to their statistical importance, a surrogate for the FI O2 /Pa O2 relationship is included, conscious level is assessed using a simplified alert/not alert variable, and the score, trigger thresholds and response are consistent with the new non-obstetric National Early Warning Score system. The statistical and clinical early warning scores were internally validated using the validation set. The area under the receiver operating characteristic curve was 0.995 (95% CI 0.992-0.998) for the statistical score and 0.957 (95% CI 0.923-0.991) for the clinical score. Pre-existing empirically designed early warning scores were also validated in the same way for comparison. The area under the receiver operating characteristic curve was 0.955 (95% CI 0.922-0.988) for Swanton et al.'s Modified Early Obstetric Warning System, 0.937 (95% CI 0.884-0.991) for the obstetric early warning score suggested in the 2003-2005 Report on Confidential Enquiries into Maternal Deaths in the UK, and 0.973 (95% CI 0.957-0.989) for the non-obstetric National Early Warning Score. This highlights that the new clinical obstetric early warning score has an excellent ability to discriminate survivors from non-survivors in this critical care data set. Further work is needed to validate our new clinical early warning score externally in the obstetric ward environment. Anaesthesia © 2013 The Association of Anaesthetists of Great Britain and Ireland.

Implementation and Challenges of the Tsunami Warning System in the Western Mediterranean

NASA Astrophysics Data System (ADS)

Schindelé, F.; Gailler, A.; Hébert, H.; Loevenbruck, A.; Gutierrez, E.; Monnier, A.; Roudil, P.; Reymond, D.; Rivera, L.

2015-03-01

The French Tsunami Warning Center (CENALT) has been in operation since 2012. It is contributing to the North-eastern and Mediterranean (NEAM) tsunami warning and mitigation system coordinated by the United Nations Educational, Scientific, and Cultural Organization, and benefits from data exchange with several foreign institutes. This center is supported by the French Government and provides French civil-protection authorities and member states of the NEAM region with relevant messages for assessing potential tsunami risk when an earthquake has occurred in the Western Mediterranean sea or the Northeastern Atlantic Ocean. To achieve its objectives, CENALT has developed a series of innovative techniques based on recent research results in seismology for early tsunami warning, monitoring of sea level variations and detection capability, and effective numerical computation of ongoing tsunamis.

Early Warning System Implementation Guide: For Use with the National High School Center's Early Warning System Tool v2.0

ERIC Educational Resources Information Center

Therriault, Susan Bowles; Heppen, Jessica; O'Cummings, Mindee; Fryer, Lindsay; Johnson, Amy

2010-01-01

This Early Warning System (EWS) Implementation Guide is a supporting document for schools and districts that are implementing the National High School Center's Early Warning System (EWS) Tool v2.0. Developed by the National High School Center at the American Institutes for Research (AIR), the guide and tool support the establishment and…

SafeLand guidelines for landslide monitoring and early warning systems in Europe - Design and required technology

NASA Astrophysics Data System (ADS)

Bazin, S.

2012-04-01

Landslide monitoring means the comparison of landslide characteristics like areal extent, speed of movement, surface topography and soil humidity from different periods in order to assess landslide activity. An ultimate "universal" methodology for this purpose does not exist; every technology has its own advantages and disadvantages. End-users should carefully consider each one to select the methodologies that represent the best compromise between pros and cons, and are best suited for their needs. Besides monitoring technology, there are many factors governing the choice of an Early Warning System (EWS). A people-centred EWS necessarily comprises five key elements: (1) knowledge of the risks; (2) identification, monitoring, analysis and forecasting of the hazards; (3) operational centre; (4) communication or dissemination of alerts and warnings; and (5) local capabilities to respond to the warnings received. The expression "end-to-end warning system" is also used to emphasize that EWSs need to span all steps from hazard detection through to community response. The aim of the present work is to provide guidelines for establishing the different components for landslide EWSs. One of the main deliverables of the EC-FP7 SafeLand project addresses the technical and practical issues related to monitoring and early warning for landslides, and identifies the best technologies available in the context of both hazard assessment and design of EWSs. This deliverable targets the end-users and aims to facilitate the decision process by providing guidelines. For the purpose of sharing the globally accumulated expertise, a screening study was done on 14 EWSs from 8 different countries. On these bases, the report presents a synoptic view of existing monitoring methodologies and early-warning strategies and their applicability for different landslide types, scales and risk management steps. Several comprehensive checklists and toolboxes are also included to support informed decisions. The deliverable was compiled with contributions from experts on landslides, monitoring technologies, remote sensing, and social researchers from 16 European institutions. The deliverable addresses one of the main objectives of the SafeLand project, namely to merge experience and expert judgment and create synergies on European level towards guidelines for early warning and to make these results available to end-users and local stakeholders.

Tree rings provide early warning signals of jack pine mortality across a moisture gradient in the southern boreal forest

NASA Astrophysics Data System (ADS)

Mamet, S. D.; Chun, K. P.; Metsaranta, J. M.; Barr, A. G.; Johnstone, J. F.

2015-08-01

Recent declines in productivity and tree survival have been widely observed in boreal forests. We used early warning signals (EWS) in tree ring data to anticipate premature mortality in jack pine (Pinus banksiana)—an extensive and dominant species occurring across the moisture-limited southern boreal forest in North America. We sampled tree rings from 113 living and 84 dead trees in three soil moisture regimes (subxeric, submesic, subhygric) in central Saskatchewan, Canada. We reconstructed annual increments of tree basal area to investigate (1) whether we could detect EWS related to mortality of individual trees, and (2) how water availability and tree growth history may explain the mortality warning signs. EWS were evident as punctuated changes in growth patterns prior to transition to an alternative state of reduced growth before dying. This transition was likely triggered by a combination of severe drought and insect outbreak. Higher moisture availability associated with a soil moisture gradient did not appear to reduce tree sensitivity to stress-induced mortality. Our results suggest tree rings offer considerable potential for detecting critical transitions in tree growth, which are linked to premature mortality.

Determination of early warning signs for photocatalytic degradation of titanium white oil paints by means of surface analysis.

PubMed

van Driel, B A; Wezendonk, T A; van den Berg, K J; Kooyman, P J; Gascon, J; Dik, J

2017-02-05

Titanium white (TiO 2 ) has been widely used as a pigment in the 20th century. However, its most photocatalytic form (anatase) can cause severe degradation of the oil paint in which it is contained. UV light initiates TiO 2 -photocatalyzed processes in the paint film, degrading the oil binder into volatile components resulting in chalking of the paint. This will eventually lead to severe changes in the appearance of a painting. To date, limited examples of degraded works of art containing titanium white are known due to the relatively short existence of the paintings in question and the slow progress of the degradation process. However, UV light will inevitably cause degradation of paint in works of art containing photocatalytic titanium white. In this work, a method to detect early warning signs of photocatalytic degradation of unvarnished oil paint is proposed, using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Consequently, a four-stage degradation model was developed through in-depth study of TiO 2 -containing paint films in various stages of degradation. The XPS surface analysis proved very valuable for detecting early warning signs of paint degradation, whereas the AFM results provide additional confirmation and are in good agreement with bulk gloss reduction. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of the Risk-Based Early Warning Method in a Fracture-Karst Water Source, North China.

PubMed

Guo, Yongli; Wu, Qing; Li, Changsuo; Zhao, Zhenhua; Sun, Bin; He, Shiyi; Jiang, Guanghui; Zhai, Yuanzheng; Guo, Fang

2018-03-01

  The paper proposes a risk-based early warning considering characteristics of fracture-karst aquifer in North China and applied it in a super-large fracture-karst water source. Groundwater vulnerability, types of land use, water abundance, transmissivity and spatial temporal variation of groundwater quality were chosen as indexes of the method. Weights of factors were obtained by using AHP method based on relative importance of factors, maps of factors were zoned by GIS, early warning map was conducted based on extension theory with the help of GIS, ENVI+IDL. The early warning map fused five factors very well, serious and tremendous warning areas are mainly located in northwest and east with high or relatively high transmissivity and groundwater pollutant loading, and obviously deteriorated or deteriorated trend of petroleum. The early warning map warns people where more attention should be paid, and the paper guides decision making to take appropriate protection actions in different warning levels areas.

Early identification systems for emerging foodborne hazards.

PubMed

Marvin, H J P; Kleter, G A; Prandini, A; Dekkers, S; Bolton, D J

2009-05-01

This paper provides a non-exhausting overview of early warning systems for emerging foodborne hazards that are operating in the various places in the world. Special attention is given to endpoint-focussed early warning systems (i.e. ECDC, ISIS and GPHIN) and hazard-focussed early warning systems (i.e. FVO, RASFF and OIE) and their merit to successfully identify a food safety problem in an early stage is discussed. Besides these early warning systems which are based on monitoring of either disease symptoms or hazards, also early warning systems and/or activities that intend to predict the occurrence of a food safety hazard in its very beginning of development or before that are described. Examples are trend analysis, horizon scanning, early warning systems for mycotoxins in maize and/or wheat and information exchange networks (e.g. OIE and GIEWS). Furthermore, recent initiatives that aim to develop predictive early warning systems based on the holistic principle are discussed. The assumption of the researchers applying this principle is that developments outside the food production chain that are either directly or indirectly related to the development of a particular food safety hazard may also provide valuable information to predict the development of this hazard.

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

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2016-01-01

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).

A topology visualization early warning distribution algorithm for large-scale network security incidents.

PubMed

He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

2013-01-01

It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

Technology, conflict early warning systems, public health, and human rights.

PubMed

Pham, Phuong N; Vinck, Patrick

2012-12-15

Public health and conflict early warning are evolving rapidly in response to technology changes for the gathering, management, analysis and communication of data. It is expected that these changes will provide an unprecedented ability to monitor, detect, and respond to crises. One of the potentially most profound and lasting expected change affects the roles of the various actors in providing and sharing information and in responding to early warning. Communities and civil society actors have the opportunity to be empowered as a source of information, analysis, and response, while the role of traditional actors shifts toward supporting those communities and building resilience. However, by creating new roles, relationships, and responsibilities, technology changes raise major concerns and ethical challenges for practitioners, pressing the need for practical guidelines and actionable recommendations in line with existing ethical principles. Copyright © 2012 Pham and Vinck. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

Early Warning Systems Assure Safe Schools

ERIC Educational Resources Information Center

Greenhalgh, John

1973-01-01

Fairfield, Connecticut, public schools are protected by an automatic fire detection system covering every area of every building through an electric monitor. An intrusion alarm system that relies primarily on pulsed infra-red beams protects the plant investment. (Author/MF)

A tsunami early warning system for the coastal area modeling

NASA Astrophysics Data System (ADS)

Soebroto, Arief Andy; Sunaryo, Suhartanto, Ery

2015-04-01

The tsunami disaster is a potential disaster in the territory of Indonesia. Indonesia is an archipelago country and close to the ocean deep. The tsunami occurred in Aceh province in 2004. Early prevention efforts have been carried out. One of them is making "tsunami buoy" which has been developed by BPPT. The tool puts sensors on the ocean floor near the coast to detect earthquakes on the ocean floor. Detection results are transmitted via satellite by a transmitter placed floating on the sea surface. The tool will cost billions of dollars for each system. Another constraint was the transmitter theft "tsunami buoy" in the absence of guard. In this study of the system has a transmission system using radio frequency and focused on coastal areas where costs are cheaper, so that it can be applied at many beaches in Indonesia are potentially affected by the tsunami. The monitoring system sends the detection results to the warning system using a radio frequency with a capability within 3 Km. Test results on the sub module sensor monitoring system generates an error of 0.63% was taken 10% showed a good quality sensing. The test results of data transmission from the transceiver of monitoring system to the receiver of warning system produces 100% successful delivery and reception of data. The test results on the whole system to function 100% properly.

Ballistic Missile Early Warning System Clear Air Force Station, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Ballistic Missile Early Warning System - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Development of a Global Agricultural Hotspot Detection and Early Warning System

NASA Astrophysics Data System (ADS)

Lemoine, G.; Rembold, F.; Urbano, F.; Csak, G.

2015-12-01

The number of web based platforms for crop monitoring has grown rapidly over the last years and anomaly maps and time profiles of remote sensing derived indicators can be accessed online thanks to a number of web based portals. However, while these systems make available a large amount of crop monitoring data to the agriculture and food security analysts, there is no global platform which provides agricultural production hotspot warning in a highly automatic and timely manner. Therefore a web based system providing timely warning evidence as maps and short narratives is currently under development by the Joint Research Centre. The system (called "HotSpot Detection System of Agriculture Production Anomalies", HSDS) will focus on water limited agricultural systems worldwide. The automatic analysis of relevant meteorological and vegetation indicators at selected administrative units (Gaul 1 level) will trigger warning messages for the areas where anomalous conditions are observed. The level of warning (ranging from "watch" to "alert") will depend on the nature and number of indicators for which an anomaly is detected. Information regarding the extent of the agricultural areas concerned by the anomaly and the progress of the agricultural season will complement the warning label. In addition, we are testing supplementary detailed information from other sources for the areas triggering a warning. These regard the automatic web-based and food security-tailored analysis of media (using the JRC Media Monitor semantic search engine) and the automatic detection of active crop area using Sentinel 1, upcoming Sentinel-2 and Landsat 8 imagery processed in Google Earth Engine. The basic processing will be fully automated and updated every 10 days exploiting low resolution rainfall estimates and satellite vegetation indices. Maps, trend graphs and statistics accompanied by short narratives edited by a team of crop monitoring experts, will be made available on the website on a monthly basis.

MACROINVERTEBRATE INVENTORIES OF THE WHITE RIVER, COLORADO AND UTAH: SIGNIFICANCE OF ANNUAL, SEASONAL, AND SPATIAL VARIATION IN THE DESIGN OF BIOMONITORING NETWORKS FOR POLLUTION DETECTION

EPA Science Inventory

An aquatic macroinvertebrate monitoring program is suggested for 'early warning' detection of toxic discharges to streams in oil shale development areas. Changes in stream biota are used to signal need for increasing levels of chemical analyses to identify and quantify toxic poll...

People-centred landslide early warning systems in the context of risk management

NASA Astrophysics Data System (ADS)

Haß, S.; Asch, K.; Fernandez-Steeger, T.; Arnhardt, C.

2009-04-01

In the current hazard research people-centred warning becomes more and more important, because different types of organizations and groups have to be involved in the warning process. This fact has to be taken into account when developing early warning systems. The effectiveness of early warning depends not only on technical capabilities but also on the preparedness of decision makers and their immediate response on how to act in case of emergency. Hence early warning systems have to be regarded in the context of an integrated and holistic risk management. Disaster Risk Reduction (DRR) measures include people-centred, timely and understandable warning. Further responsible authorities have to be identified in advance and standards for risk communication have to be established. Up to now, hazard and risk assessment for geohazards focuses on the development of inventory, susceptibility, hazard and risk maps. But often, especially in Europe, there are no institutional structures for managing geohazards and in addition there is a lack of an authority that is legally obliged to alarm on landslides at national or regional level. One of the main characteristics within the warning process for natural hazards e.g. in Germany is the split of responsibility between scientific authorities (wissenschaftliche Fachbehörde) and enforcement authorities (Vollzugsbehörde). The scientific authority provides the experts who define the methods and measures for monitoring and evaluate the hazard level. The main focus is the acquisition and evaluation of data and subsequently the distribution of information. The enforcement authority issues official warnings about dangerous natural phenomena. Hence the information chain in the context of early warning ranges over two different institutions, the forecast service and the warning service. But there doesn't exist a framework for warning processes in terms of landslides as yet. The concept for managing natural disasters is often reduced to hazard assessment and emergency response. Great importance is attached to the scientific understanding of hazards and protective structures, while analysis of socio-economic impacts and risk assessment are not considered enough. The reduction of vulnerability has to be taken into greater account. Also the information needs of different stakeholders have to be identified at an early stage and should be integrated in the development of early warning systems. The content of the warning message must be simple, understandable and should cover instructions on how to react. Further the timeliness of the messages has to be guarented. In this context the aim of the landslide monitoring and early warning system SLEWS (Sensor Based Landslide Early Warning System) is to integrate the above mentioned aspects of a holistic disaster and risk management. The technology of spatial data infrastructures and web services provides the use of multiple communication channels within an early warning system. Thus people-centred early warning messages and information about slope stability can be sent in nearly real-time. It has to be underlined that the technological information process is just one element of an effective warning system. Moreover the warning system has also to be considered as a social system and has to make allowance to socio-economic and gender aspects : «[...] Develop early warning systems that are people centered, in particular systems whose warnings are timely and understandable to those at risk, which take into account the demographic, gender, cultural and livelihood characteristics of the target audiences, including guidance on how to act upon warnings, and that support effective operations by disaster managers and other decision makers » (Hyogo Framework, 2005) References : UNITED NATIONS INTERNATIONAL STRATEGY FOR DISASTER REDUCTION SECRETARIAT (UNISDR) (2006): Developing early warning systems: a checklist, Third international conference on early warning (EWC III): from concept to action: 27-29 March 2006, Bonn, Germany. Geneva, Switzerland: International Strategy for Disaster Reduction. WORLD CONFERENCE ON DISASTER REDUCTION (2005) : Report of the World Conference on Disaster Reduction: Kobe, Hyogo, Japan, 18-22 January 2005. Geneva, Switzerland, Secretariat, World Conference on Disaster Reduction. INTER-AGENCY SECRETARIAT OF THE ISDR & GLOBAL PLATFORM FOR DISASTER RISK REDUCTION (2007): Disaster risk reduction: 2007 global review. Geneva, UN, ISDR.

Alaskan Air Defense and Early Warning Systems Clear Air ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Alaskan Air Defense and Early Warning Systems - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Toward a National Early Warning System for Forest Disturbances Using Remotely Sensed Canopy Phenology

DOE Office of Scientific and Technical Information (OSTI.GOV)

HargroveJr., William Walter; Spruce, Joe; Gasser, Gerry

2009-01-01

Imagine a national system with the ability to quickly identify forested areas under attack from insects or disease. Such an early warning system might minimize surprises such as the explosion of caterpillars referred to in the quotation to the left. Moderate resolution (ca. 500m) remote sensing repeated at frequent (ca. weekly) intervals could power such a monitoring system that would respond in near real-time. An ideal warning system would be national in scope, automated, able to improve its prognostic ability with experience, and would provide regular map updates online in familiar and accessible formats. Such a goal is quite ambitiousmore » - analyzing vegetation change weekly at a national scale with moderate resolution is a daunting task. The foremost challenge is discerning unusual or unexpected disturbances from the normal backdrop of seasonal and annual changes in vegetation conditions. A historical perspective is needed to define a 'baseline' for expected, normal behavior against which detected changes can be correctly interpreted. It would be necessary to combine temperature, precipitation, soils, and topographic information with the remotely sensed data to discriminate and interpret the changing vegetation conditions on the ground. Conterminous national coverage implies huge data volumes, even at a moderate resolution (250-500m), and likely requires a supercomputing capability. Finally, such a national warning system must carefully balance the rate of successful threat detection with false positives. Since 2005, the USDA Forest Service has partnered with the NASA Stennis Space Center and Oak Ridge National Laboratory to develop methods for monitoring environmental threats, including native insects and diseases, wildfire, invasive pests and pathogens, tornados, hurricanes, and hail. These tools will be instrumental in helping the Forest Service's two Environmental Threat Assessment Centers better meet their Congressional mandate to help track the health of the Nation's forests and rangelands. We envision two scales of forest monitoring: (1) a strategic, satellite-based monitoring of broad regions to identify particular locations where threats are suspected (i.e., early warning), and (2) a fine-scale, tactical tier consisting of airborne overflights and on-the-ground monitoring to check the validity of warnings from the upper tier. The tactical tier is already largely in place within the Forest Service and its State collaborators, consisting of aerial detection surveys (sketch mapping from aircraft), ground surveys, and trapping programs. However, these efforts are expensive and labor-intensive, can be dangerous, and may not provide sufficient broad-area coverage. Far from replacing the tactical tier, the national system will rely on the finer-scale efforts to confirm, validate, and attribute causes of detected forest disturbances. One important objective of the national warning system will be to help direct the focus of the tactical tier, making their efforts more cost efficient and effective.« less

A Risk-Based Multi-Objective Optimization Concept for Early-Warning Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Loschko, M.; Nowak, W.

2014-12-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources which cannot be eliminated, especially in urban regions. As matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs.In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations and the early warning time and to minimize the installation and operating costs of the monitoring network. A qualitative risk ranking is used to prioritize the known risk sources for monitoring. The unknown risk sources can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well.We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks which are valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrade) to also cover moderate, tolerable and unknown risk sources. Monitoring networks which are valid for the remaining risk also cover all other risk sources but the early-warning time suffers.The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. To avoid numerical dispersion during the transport simulations we use the particle-tracking random walk method.

Short National Early Warning Score - Developing a Modified Early Warning Score.

PubMed

Luís, Leandro; Nunes, Carla

2017-12-11

Early Warning Score (EWS) systems have been developed for detecting hospital patients clinical deterioration. Many studies show that a National Early Warning Score (NEWS) performs well in discriminating survival from death in acute medical and surgical hospital wards. NEWS is validated for Portugal and is available for use. A simpler EWS system may help to reduce the risk of error, as well as increase clinician compliance with the tool. The aim of the study was to evaluate whether a simplified NEWS model will improve use and data collection. We evaluated the ability of single and aggregated parameters from the NEWS model to detect patients' clinical deterioration in the 24h prior to an outcome. There were 2 possible outcomes: Survival vs Unanticipated intensive care unit admission or death. We used binary logistic regression models and Receiver Operating Characteristic Curves (ROC) to evaluate the parameters' performance in discriminating among the outcomes for a sample of patients from 6 Portuguese hospital wards. NEWS presented an excellent discriminating capability (Area under the Curve of ROC (AUCROC)=0.944). Temperature and systolic blood pressure (SBP) parameters did not contribute significantly to the model. We developed two different models, one without temperature, and the other by removing temperature and SBP (M2). Both models had an excellent discriminating capability (AUCROC: 0.965; 0.903, respectively) and a good predictive power in the optimum threshold of the ROC curve. The 3 models revealed similar discriminant capabilities. Although the use of SBP is not clearly evident in the identification of clinical deterioration, it is recognized as an important vital sign. We recommend the use of the first new model, as its simplicity may help to improve adherence and use by health care workers. Copyright © 2017 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings

PubMed Central

Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S. Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Background Dengue outbreaks are increasing in frequency over space and time, affecting people’s health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. Methods We report on the development of the EWARS tool, based on users’ recommendations into a convenient, user-friendly and reliable software aided by a user’s workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. Findings 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. Conclusion EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities. PMID:29727447

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings.

PubMed

Hussain-Alkhateeb, Laith; Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

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

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2015-10-01

The paper proposes the evaluation of the technical performance of a regional landslide early warning system by means of an original approach, called EDuMaP method, comprising three successive steps: identification and analysis of the Events (E), i.e. landslide events and warning events derived from available landslides and warnings databases; definition and computation of a Duration Matrix (DuMa), 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 (P) by means of performance criteria and indicators applied to the duration matrix. During the first step, the analyst takes into account the features of the warning model by means of ten input parameters, which are used to identify and classify landslide and warning events according to their spatial and temporal characteristics. In the second step, the analyst computes a time-based duration matrix having 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 proposed method is based on a framework clearly distinguishing between local and regional landslide early warning systems as well as among correlation laws, warning models and warning systems. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warnings data from the municipal early warning system operating in Rio de Janeiro (Brazil).

Sensor and Processing COI (Briefing Charts)

DTIC Science & Technology

2014-05-27

Persistent Surveillance • Target Detection, Recognition & ID at Standoff Ranges • Force/Platform/Sensor Protection • Target Tracking • Early Warning • BDA ...inhomogeneous and complex media is also a foundational challenge for President’s BRAIN initiative. 38 Explore Advanced Sensors And Processing

Crowd-Sourced Global Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Minson, S. E.; Brooks, B. A.; Glennie, C. L.; Murray, J. R.; Langbein, J. O.; Owen, S. E.; Iannucci, B. A.; Hauser, D. L.

2014-12-01

Although earthquake early warning (EEW) has shown great promise for reducing loss of life and property, it has only been implemented in a few regions due, in part, to the prohibitive cost of building the required dense seismic and geodetic networks. However, many cars and consumer smartphones, tablets, laptops, and similar devices contain low-cost versions of the same sensors used for earthquake monitoring. If a workable EEW system could be implemented based on either crowd-sourced observations from consumer devices or very inexpensive networks of instruments built from consumer-quality sensors, EEW coverage could potentially be expanded worldwide. Controlled tests of several accelerometers and global navigation satellite system (GNSS) receivers typically found in consumer devices show that, while they are significantly noisier than scientific-grade instruments, they are still accurate enough to capture displacements from moderate and large magnitude earthquakes. The accuracy of these sensors varies greatly depending on the type of data collected. Raw coarse acquisition (C/A) code GPS data are relatively noisy. These observations have a surface displacement detection threshold approaching ~1 m and would thus only be useful in large Mw 8+ earthquakes. However, incorporating either satellite-based differential corrections or using a Kalman filter to combine the raw GNSS data with low-cost acceleration data (such as from a smartphone) decreases the noise dramatically. These approaches allow detection thresholds as low as 5 cm, potentially enabling accurate warnings for earthquakes as small as Mw 6.5. Simulated performance tests show that, with data contributed from only a very small fraction of the population, a crowd-sourced EEW system would be capable of warning San Francisco and San Jose of a Mw 7 rupture on California's Hayward fault and could have accurately issued both earthquake and tsunami warnings for the 2011 Mw 9 Tohoku-oki, Japan earthquake.

Automatic early warning of tail biting in pigs: 3D cameras can detect lowered tail posture before an outbreak

PubMed Central

Jack, Mhairi; Futro, Agnieszka; Talbot, Darren; Zhu, Qiming; Barclay, David; Baxter, Emma M.

2018-01-01

Tail biting is a major welfare and economic problem for indoor pig producers worldwide. Low tail posture is an early warning sign which could reduce tail biting unpredictability. Taking a precision livestock farming approach, we used Time-of-flight 3D cameras, processing data with machine vision algorithms, to automate the measurement of pig tail posture. Validation of the 3D algorithm found an accuracy of 73.9% at detecting low vs. not low tails (Sensitivity 88.4%, Specificity 66.8%). Twenty-three groups of 29 pigs per group were reared with intact (not docked) tails under typical commercial conditions over 8 batches. 15 groups had tail biting outbreaks, following which enrichment was added to pens and biters and/or victims were removed and treated. 3D data from outbreak groups showed the proportion of low tail detections increased pre-outbreak and declined post-outbreak. Pre-outbreak, the increase in low tails occurred at an increasing rate over time, and the proportion of low tails was higher one week pre-outbreak (-1) than 2 weeks pre-outbreak (-2). Within each batch, an outbreak and a non-outbreak control group were identified. Outbreak groups had more 3D low tail detections in weeks -1, +1 and +2 than their matched controls. Comparing 3D tail posture and tail injury scoring data, a greater proportion of low tails was associated with more injured pigs. Low tails might indicate more than just tail biting as tail posture varied between groups and over time and the proportion of low tails increased when pigs were moved to a new pen. Our findings demonstrate the potential for a 3D machine vision system to automate tail posture detection and provide early warning of tail biting on farm. PMID:29617403

Novel Algorithms Enabling Rapid, Real-Time Earthquake Monitoring and Tsunami Early Warning Worldwide

NASA Astrophysics Data System (ADS)

Lomax, A.; Michelini, A.

2012-12-01

We have introduced recently new methods to determine rapidly the tsunami potential and magnitude of large earthquakes (e.g., Lomax and Michelini, 2009ab, 2011, 2012). To validate these methods we have implemented them along with other new algorithms within the Early-est earthquake monitor at INGV-Rome (http://early-est.rm.ingv.it, http://early-est.alomax.net). Early-est is a lightweight software package for real-time earthquake monitoring (including phase picking, phase association and event detection, location, magnitude determination, first-motion mechanism determination, ...), and for tsunami early warning based on discriminants for earthquake tsunami potential. In a simulation using archived broadband seismograms for the devastating M9, 2011 Tohoku earthquake and tsunami, Early-est determines: the epicenter within 3 min after the event origin time, discriminants showing very high tsunami potential within 5-7 min, and magnitude Mwpd(RT) 9.0-9.2 and a correct shallow-thrusting mechanism within 8 min. Real-time monitoring with Early-est givess similar results for most large earthquakes using currently available, real-time seismogram data. Here we summarize some of the key algorithms within Early-est that enable rapid, real-time earthquake monitoring and tsunami early warning worldwide: >>> FilterPicker - a general purpose, broad-band, phase detector and picker (http://alomax.net/FilterPicker); >>> Robust, simultaneous association and location using a probabilistic, global-search; >>> Period-duration discriminants TdT0 and TdT50Ex for tsunami potential available within 5 min; >>> Mwpd(RT) magnitude for very large earthquakes available within 10 min; >>> Waveform P polarities determined on broad-band displacement traces, focal mechanisms obtained with the HASH program (Hardebeck and Shearer, 2002); >>> SeisGramWeb - a portable-device ready seismogram viewer using web-services in a browser (http://alomax.net/webtools/sgweb/info.html). References (see also: http://alomax.net/pub_list.html): Lomax, A. and A. Michelini (2012), Tsunami early warning within 5 minutes, Pure and Applied Geophysics, 169, nnn-nnn, doi: 10.1007/s00024-012-0512-6. Lomax, A. and A. Michelini (2011), Tsunami early warning using earthquake rupture duration and P-wave dominant period: the importance of length and depth of faulting, Geophys. J. Int., 185, 283-291, doi: 10.1111/j.1365-246X.2010.04916.x. Lomax, A. and A. Michelini (2009b), Tsunami early warning using earthquake rupture duration, Geophys. Res. Lett., 36, L09306, doi:10.1029/2009GL037223. Lomax, A. and A. Michelini (2009a), Mwpd: A Duration-Amplitude Procedure for Rapid Determination of Earthquake Magnitude and Tsunamigenic Potential from P Waveforms, Geophys. J. Int.,176, 200-214, doi:10.1111/j.1365-246X.2008.03974.x

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

PubMed Central

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-01-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. PMID:28257073

ForWarn: A Cross-Cutting Forest Resource Management and Decision Support System Providing the Capacity to Identify and Track Forest Disturbances Nationally

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Spruce, J.; Norman, S.; Christie, W.; Hoffman, F. M.

2012-12-01

The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. It has operated as a prototype since January 2010 and has provided useful information about the location and extent of disturbances detected during the 2011 growing season, including tornadoes, wildfires, and extreme drought. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the web through the ForWarn Change Assessment Viewer at http://forwarn.forestthreats.org/fcav. No user id or password is required, and there is no cost. The Assessment Viewer operates within any popular web browser using nearly any type of computer. It lets users pan, zoom, and scroll around within ForWarn maps, and also contains an up-to-date library of co-registered, near real-time ancillary maps from diverse sources that allows users to assess the nature of particular forest disturbances and ascribe their most-likely causes. Users can check the current week's U.S. Drought Monitor, USGS VegDRI maps, FHM Historical Aerial Disturbance Surveys, MODIS Cumulative Current Year Fire Detections, and many others. A "Share this map" feature lets users save the current map view and extent into a web URL, so that users can easily share what they are looking at inside the Assessment Viewer with others via an email, a document, or a web page. The ForWarn Rapid National Assessment Team examined more than 60 ForWarn forest disturbance events in 2011-2012, and issued over 30 alerts. We hope to automate forest disturbance alerts and supply them through various subscription services. Forest owners and managers would only be alerted to disturbances occurring near their own forest resources.

Air quality early-warning system for cities in China

NASA Astrophysics Data System (ADS)

Xu, Yunzhen; Yang, Wendong; Wang, Jianzhou

2017-01-01

Air pollution has become a serious issue in many developing countries, especially in China, and could generate adverse effects on human beings. Air quality early-warning systems play an increasingly significant role in regulatory plans that reduce and control emissions of air pollutants and inform the public in advance when harmful air pollution is foreseen. However, building a robust early-warning system that will improve the ability of early-warning is not only a challenge but also a critical issue for the entire society. Relevant research is still poor in China and cannot always satisfy the growing requirements of regulatory planning, despite the issue's significance. Therefore, in this paper, a hybrid air quality early-warning system was successfully developed, composed of forecasting and evaluation. First, a hybrid forecasting model was proposed as an important part of this system based on the theory of "decomposition and ensemble" and combined with the advanced data processing technique, support vector machine, the latest bio-inspired optimization algorithm and the leave-one-out strategy for deciding weights. Afterwards, to intensify the research, fuzzy evaluation was performed, which also plays an indispensable role in the early-warning system. The forecasting model and fuzzy evaluation approaches are complementary. Case studies using daily air pollution concentrations of six air pollutants from three cities in China (i.e., Taiyuan, Harbin and Chongqing) are used as examples to evaluate the efficiency and effectiveness of the developed air quality early-warning system. Experimental results demonstrate that both the accuracy and the effectiveness of the developed system are greatly superior for air quality early warning. Furthermore, the application of forecasting and evaluation enables the informative and effective quantification of future air quality, offering a significant advantage, and can be employed to develop rapid air quality early-warning systems.

No evidence of critical slowing down in two endangered Hawaiian honeycreepers

PubMed Central

Camp, Richard J.; Reed, J. Michael

2017-01-01

There is debate about the current population trends and predicted short-term fates of the endangered forest birds, Hawai`i Creeper (Loxops mana) and Hawai`i `Ākepa (L. coccineus). Using long-term population size estimates, some studies report forest bird populations as stable or increasing, while other studies report signs of population decline or impending extinction associated with introduced Japanese White-eye (Zosterops japonicus) increase. Reliable predictors of impending population collapse, well before the collapse begins, have been reported in simulations and microcosm experiments. In these studies, statistical indicators of critical slowing down, a phenomenon characterized by longer recovery rates after population size perturbation, are reported to be early warning signals of an impending regime shift observable prior to the tipping point. While the conservation applications of these metrics are commonly discussed, early warning signal detection methods are rarely applied to population size data from natural populations, so their efficacy and utility in species management remain unclear. We evaluated two time series of state-space abundance estimates (1987–2012) from Hakalau Forest National Wildlife Refuge, Hawai`i to test for evidence of early warning signals of impending population collapse for the Hawai`i Creeper and Hawai`i `Ākepa. We looked for signals throughout the time series, and prior to 2000, when white-eye abundance began increasing. We found no evidence for either species of increasing variance, autocorrelation, or skewness, which are commonly reported early warning signals. We calculated linear rather than ordinary skewness because the latter is biased, particularly for small sample sizes. Furthermore, we identified break-points in trends over time for both endangered species, indicating shifts in slopes away from strongly increasing trends, but they were only weakly supported by Bayesian change-point analyses (i.e., no step-wise changes in abundance). The break-point and change-point test results, in addition to the early warning signal analyses, support that the two populations do not appear to show signs of critical slowing down or decline. PMID:29131835

No evidence of critical slowing down in two endangered Hawaiian honeycreepers

USGS Publications Warehouse

Rozek, Jessica C.; Camp, Richard J.; Reed, J. Michael

2017-01-01

There is debate about the current population trends and predicted short-term fates of the endangered forest birds, Hawai`i Creeper (Loxops mana) and Hawai`i `Ākepa (L. coccineus). Using long-term population size estimates, some studies report forest bird populations as stable or increasing, while other studies report signs of population decline or impending extinction associated with introduced Japanese White-eye (Zosterops japonicus) increase. Reliable predictors of impending population collapse, well before the collapse begins, have been reported in simulations and microcosm experiments. In these studies, statistical indicators of critical slowing down, a phenomenon characterized by longer recovery rates after population size perturbation, are reported to be early warning signals of an impending regime shift observable prior to the tipping point. While the conservation applications of these metrics are commonly discussed, early warning signal detection methods are rarely applied to population size data from natural populations, so their efficacy and utility in species management remain unclear. We evaluated two time series of state-space abundance estimates (1987–2012) from Hakalau Forest National Wildlife Refuge, Hawai`i to test for evidence of early warning signals of impending population collapse for the Hawai`i Creeper and Hawai`i `Ākepa. We looked for signals throughout the time series, and prior to 2000, when white-eye abundance began increasing. We found no evidence for either species of increasing variance, autocorrelation, or skewness, which are commonly reported early warning signals. We calculated linear rather than ordinary skewness because the latter is biased, particularly for small sample sizes. Furthermore, we identified break-points in trends over time for both endangered species, indicating shifts in slopes away from strongly increasing trends, but they were only weakly supported by Bayesian change-point analyses (i.e., no step-wise changes in abundance). The break-point and change-point test results, in addition to the early warning signal analyses, support that the two populations do not appear to show signs of critical slowing down or decline.

Urban Flood Prevention and Early Warning System in Jinan City

NASA Astrophysics Data System (ADS)

Feng, Shiyuan; Li, Qingguo

2018-06-01

The system construction of urban flood control and disaster reduction in China is facing pressure and challenge from new urban water disaster. Under the circumstances that it is difficult to build high standards of flood protection engineering measures in urban areas, it is particularly important to carry out urban flood early warning. In Jinan City, a representative inland area, based on the index system of early warning of flood in Jinan urban area, the method of fuzzy comprehensive evaluation was adopted to evaluate the level of early warning. Based on the cumulative rainfall of 3 hours, the CAflood simulation results based on cellular automaton model of urban flooding were used as evaluation indexes to realize the accuracy and integration of urban flood control early warning.

Improvement of real-time seismic magnitude estimation by combining seismic and geodetic instrumentation

NASA Astrophysics Data System (ADS)

Goldberg, D.; Bock, Y.; Melgar, D.

2017-12-01

Rapid seismic magnitude assessment is a top priority for earthquake and tsunami early warning systems. For the largest earthquakes, seismic instrumentation tends to underestimate the magnitude, leading to an insufficient early warning, particularly in the case of tsunami evacuation orders. GPS instrumentation provides more accurate magnitude estimations using near-field stations, but isn't sensitive enough to detect the first seismic wave arrivals, thereby limiting solution speed. By optimally combining collocated seismic and GPS instruments, we demonstrate improved solution speed of earthquake magnitude for the largest seismic events. We present a real-time implementation of magnitude-scaling relations that adapts to consider the length of the recording, reflecting the observed evolution of ground motion with time.

Technical implementation plan for the ShakeAlert production system: an Earthquake Early Warning system for the West Coast of the United States

USGS Publications Warehouse

Given, Douglas D.; Cochran, Elizabeth S.; Heaton, Thomas; Hauksson, Egill; Allen, Richard; Hellweg, Peggy; Vidale, John; Bodin, Paul

2014-01-01

Earthquake Early Warning (EEW) systems can provide as much as tens of seconds of warning to people and automated systems before strong shaking arrives. The United States Geological Survey (USGS) and its partners are developing such an EEW system, called ShakeAlert, for the West Coast of the United States. This document describes the technical implementation of that system, which leverages existing stations and infrastructure of the Advanced National Seismic System (ANSS) regional networks to achieve this new capability. While significant progress has been made in developing the ShakeAlert early warning system, improved robustness of each component of the system and additional testing and certification are needed for the system to be reliable enough to issue public alerts. Major components of the system include dense networks of ground motion sensors, telecommunications from those sensors to central processing systems, algorithms for event detection and alert creation, and distribution systems to alert users. Capital investment costs for a West Coast EEW system are projected to be $38.3M, with additional annual maintenance and operations totaling $16.1M—in addition to current ANSS expenditures for earthquake monitoring. An EEW system is complementary to, but does not replace, other strategies to mitigate earthquake losses. The system has limitations: false and missed alerts are possible, and the area very near to an earthquake epicenter may receive little or no warning. However, such an EEW system would save lives, reduce injuries and damage, and improve community resilience by reducing longer-term economic losses for both public and private entities.

The Earthquake Early Warning System in Japan (Invited)

NASA Astrophysics Data System (ADS)

Mori, J. J.; Yamada, M.

2010-12-01

In Japan, the earthquake early warning system (Kinkyu Jishin Sokuhou in Japanese) maintained by the Japan Meterological Agency (JMA) has been in operation and sending pubic information since October 1, 2007. Messages have been broadcast on television and radio to warn of strong shaking to the public. The threshold for broadcasting a message is an estimated intensity of JMA 5 lower, which is approximately equivalent to MM VII to VIII. During the period from October 2007 through August 2010, messages have been sent 9 times for earthquakes of magnitude 5.2 to 7.0. There have been a few instances of significantly over-estimating or under-estimating the predicted shaking, but in general the performance of the system has been quite good. The quality of the detection system depends on the dense network of high-quality seismometers that cover the Japanese Islands. Consequently, the system works very well for events on or close to the 4 main islands, but there is more uncertainty for events near the smaller and more distant islands where the density of instrumentation is much less The Early Warning System is also tied to an extensive education program so that the public can react appropriately in the short amount of time given by the warning. There appears to be good public support in Japan, where people have become accustomed to a high level of fast information on a daily basis. There has also been development of a number of specific safety applications in schools and industry that work off the backbone information provided in the national system.

Earthquake early warning for Romania - most recent improvements

NASA Astrophysics Data System (ADS)

Marmureanu, Alexandru; Elia, Luca; Martino, Claudio; Colombelli, Simona; Zollo, Aldo; Cioflan, Carmen; Toader, Victorin; Marmureanu, Gheorghe; Marius Craiu, George; Ionescu, Constantin

2014-05-01

EWS for Vrancea earthquakes uses the time interval (28-32 sec.) between the moment when the earthquake is detected by the local seismic network installed in the epicenter area (Vrancea) and the arrival time of the seismic waves in the protected area (Bucharest) to send earthquake warning to users. In the last years, National Institute for Earth Physics (NIEP) upgraded its seismic network in order to cover better the seismic zones of Romania. Currently the National Institute for Earth Physics (NIEP) operates a real-time seismic network designed to monitor the seismic activity on the Romania territory, dominated by the Vrancea intermediate-depth (60-200 km) earthquakes. The NIEP real-time network consists of 102 stations and two seismic arrays equipped with different high quality digitizers (Kinemetrics K2, Quanterra Q330, Quanterra Q330HR, PS6-26, Basalt), broadband and short period seismometers (CMG3ESP, CMG40T, KS2000, KS54000, KS2000, CMG3T,STS2, SH-1, S13, Ranger, gs21, Mark l22) and acceleration sensors (Episensor). Recent improvement of the seismic network and real-time communication technologies allows implementation of a nation-wide EEWS for Vrancea and other seismic sources from Romania. We present a regional approach to Earthquake Early Warning for Romania earthquakes. The regional approach is based on PRESTo (Probabilistic and Evolutionary early warning SysTem) software platform: PRESTo processes in real-time three channel acceleration data streams: once the P-waves arrival have been detected, it provides earthquake location and magnitude estimations, and peak ground motion predictions at target sites. PRESTo is currently implemented in real- time at National Institute for Earth Physics, Bucharest for several months in parallel with a secondary EEWS. The alert notification is issued only when both systems validate each other. Here we present the results obtained using offline earthquakes originating from Vrancea area together with several real-time detection of significant earthquakes from Vrancea and Transylvania areas that occurred in the last months. Currently the warning notification is sent to several users including emergency response units from 12 counties, a big bridge located in Bucharest, a nuclear sterilization facility in Măgurele city and to the nuclear power plant from Cernavoda.

Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection.

PubMed

Olson, Sarah H; Benedum, Corey M; Mekaru, Sumiko R; Preston, Nicholas D; Mazet, Jonna A K; Joly, Damien O; Brownstein, John S

2015-08-01

The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data.

Early warning signal for dengue outbreaks and identification of high risk areas for dengue fever in Colombia using climate and non-climate datasets.

PubMed

Lee, Jung-Seok; Carabali, Mabel; Lim, Jacqueline K; Herrera, Victor M; Park, Il-Yeon; Villar, Luis; Farlow, Andrew

2017-07-10

Dengue has been prevalent in Colombia with high risk of outbreaks in various locations. While the prediction of dengue epidemics will bring significant benefits to the society, accurate forecasts have been a challenge. Given competing health demands in Colombia, it is critical to consider the effective use of the limited healthcare resources by identifying high risk areas for dengue fever. The Climate Risk Factor (CRF) index was constructed based upon temperature, precipitation, and humidity. Considering the conditions necessary for vector survival and transmission behavior, elevation and population density were taken into account. An Early Warning Signal (EWS) model was developed by estimating the elasticity of the climate risk factor function to detect dengue epidemics. The climate risk factor index was further estimated at the smaller geographical unit (5 km by 5 km resolution) to identify populations at high risk. From January 2007 to December 2015, the Early Warning Signal model successfully detected 75% of the total number of outbreaks 1 ~ 5 months ahead of time, 12.5% in the same month, and missed 12.5% of all outbreaks. The climate risk factors showed that populations at high risk are concentrated in the Western part of Colombia where more suitable climate conditions for vector mosquitoes and the high population level were observed compared to the East. This study concludes that it is possible to detect dengue outbreaks ahead of time and identify populations at high risk for various disease prevention activities based upon observed climate and non-climate information. The study outcomes can be used to minimize potential societal losses by prioritizing limited healthcare services and resources, as well as by conducting vector control activities prior to experiencing epidemics.

Sustained live poultry market surveillance contributes to early warnings for human infection with avian influenza viruses.

PubMed

Fang, Shisong; Bai, Tian; Yang, Lei; Wang, Xin; Peng, Bo; Liu, Hui; Geng, Yijie; Zhang, Renli; Ma, Hanwu; Zhu, Wenfei; Wang, Dayan; Cheng, Jinquan; Shu, Yuelong

2016-08-03

Sporadic human infections with the highly pathogenic avian influenza (HPAI) A (H5N6) virus have been reported in different provinces in China since April 2014. From June 2015 to January 2016, routine live poultry market (LPM) surveillance was conducted in Shenzhen, Guangdong Province. H5N6 viruses were not detected until November 2015. The H5N6 virus-positive rate increased markedly beginning in December 2015, and viruses were detected in LPMs in all districts of the city. Coincidently, two human cases with histories of poultry exposure developed symptoms and were diagnosed as H5N6-positive in Shenzhen during late December 2015 and early January 2016. Similar viruses were identified in environmental samples collected in the LPMs and the patients. In contrast to previously reported H5N6 viruses, viruses with six internal genes derived from the H9N2 or H7N9 viruses were detected in the present study. The increased H5N6 virus-positive rate in the LPMs and the subsequent human infections demonstrated that sustained LPM surveillance for avian influenza viruses provides an early warning for human infections. Interventions, such as LPM closures, should be immediately implemented to reduce the risk of human infection with the H5N6 virus when the virus is widely detected during LPM surveillance.

Technology-Based Early Warning Systems for Bipolar Disorder: A Conceptual Framework

PubMed Central

Torous, John; Thompson, Wesley

2016-01-01

Recognition and timely action around “warning signs” of illness exacerbation is central to the self-management of bipolar disorder. Due to its heterogeneity and fluctuating course, passive and active mobile technologies have been increasingly evaluated as adjunctive or standalone tools to predict and prevent risk of worsening of course in bipolar disorder. As predictive analytics approaches to big data from mobile health (mHealth) applications and ancillary sensors advance, it is likely that early warning systems will increasingly become available to patients. Such systems could reduce the amount of time spent experiencing symptoms and diminish the immense disability experienced by people with bipolar disorder. However, in addition to the challenges in validating such systems, we argue that early warning systems may not be without harms. Probabilistic warnings may be delivered to individuals who may not be able to interpret the warning, have limited information about what behaviors to change, or are unprepared to or cannot feasibly act due to time or logistic constraints. We propose five essential elements for early warning systems and provide a conceptual framework for designing, incorporating stakeholder input, and validating early warning systems for bipolar disorder with a focus on pragmatic considerations. PMID:27604265

[Ecological security early-warning in Zhoushan Islands based on variable weight model].

PubMed

Zhou, Bin; Zhong, Lin-sheng; Chen, Tian; Zhou, Rui

2015-06-01

Ecological security early warning, as an important content of ecological security research, is of indicating significance in maintaining regional ecological security. Based on driving force, pressure, state, impact and response (D-P-S-I-R) framework model, this paper took Zhoushan Islands in Zhejiang Province as an example to construct the ecological security early warning index system, test degrees of ecological security early warning of Zhoushan Islands from 2000 to 2012 by using the method of variable weight model, and forecast ecological security state of 2013-2018 by Markov prediction method. The results showed that the variable weight model could meet the study needs of ecological security early warning of Zhoushan Islands. There was a fluctuant rising ecological security early warning index from 0.286 to 0.484 in Zhoushan Islands between year 2000 and 2012, in which the security grade turned from "serious alert" into " medium alert" and the indicator light turned from "orange" to "yellow". The degree of ecological security warning was "medium alert" with the light of "yellow" for Zhoushan Islands from 2013 to 2018. These findings could provide a reference for ecological security maintenance of Zhoushan Islands.

A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 6 2011-10-01 2011-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 6 2012-10-01 2012-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 6 2010-10-01 2010-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 6 2013-10-01 2013-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 6 2014-10-01 2014-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

The Role of Cash Flow in Financial Early Warning of Agricultural Enterprises Based on Logistic Model

NASA Astrophysics Data System (ADS)

Sun, Fengru

2018-01-01

This paper chooses the agricultural listed companies as the research object, compares the financial situation of the enterprise and the theory of financial early warning, combines the financial status of the agricultural listed companies, selects the relevant cash flow indicators, discusses the application of the Logistic financial early warning model in the agricultural listed companies, Agricultural enterprises get better development. Research on financial early warning of agricultural listed companies will help the agricultural listed companies to predict the financial crisis. Financial early warning model is simple to establish, operational and strong, the use of financial early warning model, to help enterprises in the financial crisis before taking rapid and effective measures, which can avoid losses. Help enterprises to discover signs of deterioration of the financial situation in time to maintain the sustainable development of agricultural enterprises. In addition, through the financial early warning model, investors can correctly identify the financial situation of agricultural enterprises, and can evaluate the financial situation of agricultural enterprises and to help investors to invest in scientific and rational, beneficial to investors to analyze the safety of investment. But also help the relevant regulatory agencies to effectively monitor the market and promote the healthy and stable development of the market.

Awareness levels about breast cancer risk factors, early warning signs, and screening and therapeutic approaches among Iranian adult women: a large population based study using latent class analysis.

PubMed

Tazhibi, Mahdi; Feizi, Awat

2014-01-01

Breast cancer (BC) continues to be a major cause of morbidity and mortality among women throughout the world and in Iran. Lack of awareness and early detection program in developing country is a main reason for escalating the mortality. The present research was conducted to assess the Iranian women's level of knowledge about breast cancer risk factors, early warning signs, and therapeutic and screening approaches, and their correlated determinants. In a cross-sectional study, 2250 women before participating at a community based screening and public educational program in an institute of cancer research in Isfahan, Iran, in 2012 were investigated using a self-administered questionnaire about risk factors, early warning signs, and therapeutic and screening approaches of BC. Latent class regression as a comprehensive statistical method was used for evaluating the level of knowledge and its correlated determinants. Only 33.2%, 31.9%, 26.7%, and 35.8% of study participants had high awareness levels about screening approaches, risk factors, early warning signs and therapeutic modalities of breast cancer, respectively, and majority had poor to moderate knowledge levels. Most effective predictors of high level of awareness were higher educational qualifications, attending in screening and public educational programs, personal problem, and family history of BC, respectively. Results of current study indicated that the levels of awareness among study population about key elements of BC are low. These findings reenforce the continuing need for more BC education through conducting public and professional programs that are intended to raise awareness among younger, single women and those with low educational attainments and without family history.

Setting up an early warning system for epidemic-prone diseases in Darfur: a participative approach.

PubMed

Pinto, Augusto; Saeed, Mubarak; El Sakka, Hammam; Rashford, Adrienne; Colombo, Alessandro; Valenciano, Marta; Sabatinelli, Guido

2005-12-01

In April-May 2004, the World Health Organization (WHO) implemented, with local authorities, United Nations (UN) agencies and non-governmental organisations (NGOs), an early warning system (EWS) in Darfur, West Sudan, for internally displaced persons (IDPs). The number of consultations and deaths per week for 12 health events is recorded for two age groups (less than five years and five years and above). Thresholds are used to detect potential outbreaks. Ten weeks after the introduction of the system, NGOs were covering 54 camps, and 924,281 people (IDPs and the host population). Of these 54 camps, 41 (76%) were reporting regularly under the EWS. Between 22 May and 30 July, 179,795 consultations were reported: 18.7% for acute respiratory infections; 15% for malaria; 8.4% for bloody diarrhoea; and 1% for severe acute malnutrition. The EWS is useful for detecting outbreaks and monitoring the number of consultations required to trigger actions, but not for estimating mortality.

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

PubMed Central

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-01-01

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. PMID:24335727

Application of Advanced Wide Area Early Warning Systems with Adaptive Protection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blumstein, Carl; Cibulka, Lloyd; Thorp, James

2014-09-30

Recent blackouts of power systems in North America and throughout the world have shown how critical a reliable power system is to modern societies, and the enormous economic and societal damage a blackout can cause. It has been noted that unanticipated operation of protection systems can contribute to cascading phenomena and, ultimately, blackouts. This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second methodmore » detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers.« less

Fall risk assessment and early-warning for toddler behaviors at home.

PubMed

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-12-10

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network.

PubMed

Cordes, Kristina M; Cookson, Susan T; Boyd, Andrew T; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad; Husain, Farah

2017-11-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network

PubMed Central

Cordes, Kristina M.; Cookson, Susan T.; Boyd, Andrew T.; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad

2017-01-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security. PMID:29155660

Development of systems for detection, early warning, and control of pipeline leakage in drinking water distribution: a case study.

PubMed

Li, Weifeng; Ling, Wencui; Liu, Suoxiang; Zhao, Jing; Liu, Ruiping; Chen, Qiuwen; Qiang, Zhimin; Qu, Jiuhui

2011-01-01

Water leakage in drinking water distribution systems is a serious problem for many cities and a huge challenge for water utilities. An integrated system for the detection, early warning, and control of pipeline leakage has been developed and successfully used to manage the pipeline networks in selected areas of Beijing. A method based on the geographic information system has been proposed to quickly and automatically optimize the layout of the instruments which detect leaks. Methods are also proposed to estimate the probability of each pipe segment leaking (on the basis of historic leakage data), and to assist in locating the leakage points (based on leakage signals). The district metering area (DMA) strategy is used. Guidelines and a flowchart for establishing a DMA to manage the large-scale looped networks in Beijing are proposed. These different functions have been implemented into a central software system to simplify the day-to-day use of the system. In 2007 the system detected 102 non-obvious leakages (i.e., 14.2% of the total detected in Beijing) in the selected areas, which was estimated to save a total volume of 2,385,000 m3 of water. These results indicate the feasibility, efficiency and wider applicability of this system.

MyShake: A smartphone seismic network for earthquake early warning and beyond

PubMed Central

Kong, Qingkai; Allen, Richard M.; Schreier, Louis; Kwon, Young-Woo

2016-01-01

Large magnitude earthquakes in urban environments continue to kill and injure tens to hundreds of thousands of people, inflicting lasting societal and economic disasters. Earthquake early warning (EEW) provides seconds to minutes of warning, allowing people to move to safe zones and automated slowdown and shutdown of transit and other machinery. The handful of EEW systems operating around the world use traditional seismic and geodetic networks that exist only in a few nations. Smartphones are much more prevalent than traditional networks and contain accelerometers that can also be used to detect earthquakes. We report on the development of a new type of seismic system, MyShake, that harnesses personal/private smartphone sensors to collect data and analyze earthquakes. We show that smartphones can record magnitude 5 earthquakes at distances of 10 km or less and develop an on-phone detection capability to separate earthquakes from other everyday shakes. Our proof-of-concept system then collects earthquake data at a central site where a network detection algorithm confirms that an earthquake is under way and estimates the location and magnitude in real time. This information can then be used to issue an alert of forthcoming ground shaking. MyShake could be used to enhance EEW in regions with traditional networks and could provide the only EEW capability in regions without. In addition, the seismic waveforms recorded could be used to deliver rapid microseism maps, study impacts on buildings, and possibly image shallow earth structure and earthquake rupture kinematics. PMID:26933682

MyShake: A smartphone seismic network for earthquake early warning and beyond.

PubMed

Kong, Qingkai; Allen, Richard M; Schreier, Louis; Kwon, Young-Woo

2016-02-01

Large magnitude earthquakes in urban environments continue to kill and injure tens to hundreds of thousands of people, inflicting lasting societal and economic disasters. Earthquake early warning (EEW) provides seconds to minutes of warning, allowing people to move to safe zones and automated slowdown and shutdown of transit and other machinery. The handful of EEW systems operating around the world use traditional seismic and geodetic networks that exist only in a few nations. Smartphones are much more prevalent than traditional networks and contain accelerometers that can also be used to detect earthquakes. We report on the development of a new type of seismic system, MyShake, that harnesses personal/private smartphone sensors to collect data and analyze earthquakes. We show that smartphones can record magnitude 5 earthquakes at distances of 10 km or less and develop an on-phone detection capability to separate earthquakes from other everyday shakes. Our proof-of-concept system then collects earthquake data at a central site where a network detection algorithm confirms that an earthquake is under way and estimates the location and magnitude in real time. This information can then be used to issue an alert of forthcoming ground shaking. MyShake could be used to enhance EEW in regions with traditional networks and could provide the only EEW capability in regions without. In addition, the seismic waveforms recorded could be used to deliver rapid microseism maps, study impacts on buildings, and possibly image shallow earth structure and earthquake rupture kinematics.

Blaptica dubia as sentinels for exposure to chemical warfare agents - a pilot study.

PubMed

Worek, Franz; Seeger, Thomas; Neumaier, Katharina; Wille, Timo; Thiermann, Horst

2016-11-16

The increased interest of terrorist groups in toxic chemicals and chemical warfare agents presents a continuing threat to our societies. Early warning and detection is a key component for effective countermeasures against such deadly agents. Presently available and near term solutions have a number of major drawbacks, e.g. lack of automated, remote warning and detection of primarily low volatile chemical warfare agents. An alternative approach is the use of animals as sentinels for exposure to toxic chemicals. To overcome disadvantages of vertebrates the present pilot study was initiated to investigate the suitability of South American cockroaches (Blaptica dubia) as warning system for exposure to chemical warfare nerve and blister agents. Initial in vitro experiments with nerve agents showed an increasing inhibitory potency in the order tabun - cyclosarin - sarin - soman - VX of cockroach cholinesterase. Exposure of cockroaches to chemical warfare agents resulted in clearly visible and reproducible reactions, the onset being dependent on the agent and dose. With nerve agents the onset was related to the volatility of the agents. The blister agent lewisite induced signs largely comparable to those of nerve agents while sulfur mustard exposed animals exhibited a different sequence of events. In conclusion, this first pilot study indicates that Blaptica dubia could serve as a warning system to exposure of chemical warfare agents. A cockroach-based system will not detect or identify a particular chemical warfare agent but could trigger further actions, e.g. specific detection and increased protective status. By designing appropriate boxes with (IR) motion sensors and remote control (IR) camera automated off-site warning systems could be realized. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of a CO2 dial system for infrared detection of forest fire and reduction of false alarm

NASA Astrophysics Data System (ADS)

Bellecci, C.; Francucci, M.; Gaudio, P.; Gelfusa, M.; Martellucci, S.; Richetta, M.; Lo Feudo, T.

2007-04-01

Forest fires can be the cause of serious environmental and economic damages. For this reason considerable effort has been directed toward forest protection and fire fighting. The means traditionally used for early fire detection mainly consist in human observers dispersed over forest regions. A significant improvement in early warning capabilities could be obtained by using automatic detection apparatus. In order to early detect small forest fires and minimize false alarms, the use of a lidar system and dial technique will be considered. A first evaluation of the lowest detectable concentration will be estimated by numerical simulation. The theoretical model will also be used to get the capability of the dial system to control wooded areas. Fixing the burning rate for several fuels, the maximum range of detection will be evaluated. Finally results of simulations will be reported.

Clinical significance of automatic warning function of cardiac remote monitoring systems in preventing acute cardiac episodes

PubMed Central

Chen, Shou-Qiang; Xing, Shan-Shan; Gao, Hai-Qing

2014-01-01

Objective: In addition to ambulatory Holter electrocardiographic recording and transtelephonic electrocardiographic monitoring (TTM), a cardiac remote monitoring system can provide an automatic warning function through the general packet radio service (GPRS) network, enabling earlier diagnosis, treatment and improved outcome of cardiac diseases. The purpose of this study was to estimate its clinical significance in preventing acute cardiac episodes. Methods: Using 2 leads (V1 and V5 leads) and the automatic warning mode, 7160 patients were tested with a cardiac remote monitoring system from October 2004 to September 2007. If malignant arrhythmias or obvious ST-T changes appeared in the electrocardiogram records was automatically transferred to the monitoring center, the patient and his family members were informed, and the corresponding precautionary or therapeutic measures were implemented immediately. Results: In our study, 274 cases of malignant arrhythmia, including sinus standstill and ventricular tachycardia, and 43 cases of obvious ST-segment elevation were detected and treated. Because of early detection, there was no death or deformity. Conclusions: A cardiac remote monitoring system providing an automatic warning function can play an important role in preventing acute cardiac episodes. PMID:25674124

Earthquake Early Warning Management based on Client-Server using Primary Wave data from Vibrating Sensor

NASA Astrophysics Data System (ADS)

Laumal, F. E.; Nope, K. B. N.; Peli, Y. S.

2018-01-01

Early warning is a warning mechanism before an actual incident occurs, can be implemented on natural events such as tsunamis or earthquakes. Earthquakes are classified in tectonic and volcanic types depend on the source and nature. The tremor in the form of energy propagates in all directions as Primary and Secondary waves. Primary wave as initial earthquake vibrations propagates longitudinally, while the secondary wave propagates like as a sinusoidal wave after Primary, destructive and as a real earthquake. To process the primary vibration data captured by the earthquake sensor, a network management required client computer to receives primary data from sensors, authenticate and forward to a server computer to set up an early warning system. With the water propagation concept, a method of early warning system has been determined in which some sensors are located on the same line, sending initial vibrations as primary data on the same scale and the server recommended to the alarm sound as an early warning.

Massachusetts Early Warning Indicator System (EWIS). "Technical Descriptions of Risk Model Development": Early and Late Elementary Age Groupings (Grades 1-6)

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…

A Walk through TRIDEC's intermediate Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Hammitzsch, M.; Reißland, S.; Lendholt, M.

2012-04-01

The management of natural crises is an important application field of the technology developed in the project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC), co-funded by the European Commission in its Seventh Framework Programme. TRIDEC is based on the development of the German Indonesian Tsunami Early Warning System (GITEWS) and the Distant Early Warning System (DEWS) providing a service platform for both sensor integration and warning dissemination. In TRIDEC new developments in Information and Communication Technology (ICT) are used to extend the existing platform realising a component-based technology framework for building distributed tsunami warning systems for deployment, e.g. in the North-eastern Atlantic, the Mediterranean and Connected Seas (NEAM) region. The TRIDEC system will be implemented in three phases, each with a demonstrator. Successively, the demonstrators are addressing challenges, such as the design and implementation of a robust and scalable service infrastructure supporting the integration and utilisation of existing resources with accelerated generation of large volumes of data. These include sensor systems, geo-information repositories, simulation tools and data fusion tools. In addition to conventional sensors also unconventional sensors and sensor networks play an important role in TRIDEC. The system version presented is based on service-oriented architecture (SOA) concepts and on relevant standards of the Open Geospatial Consortium (OGC), the World Wide Web Consortium (W3C) and the Organization for the Advancement of Structured Information Standards (OASIS). In this way the system continuously gathers, processes and displays events and data coming from open sensor platforms to enable operators to quickly decide whether an early warning is necessary and to send personalized warning messages to the authorities and the population at large through a wide range of communication channels. The system integrates OGC Sensor Web Enablement (SWE) compliant sensor systems for the rapid detection of hazardous events, like earthquakes, sea level anomalies, ocean floor occurrences, and ground displacements. Using OGC Web Map Service (WMS) and Web Feature Service (WFS) spatial data are utilized to depict the situation picture. The integration of a simulation system to identify affected areas is considered using the OGC Web Processing Service (WPS). Warning messages are compiled and transmitted in the OASIS Common Alerting Protocol (CAP) together with addressing information defined via the OASIS Emergency Data Exchange Language - Distribution Element (EDXL-DE). The first system demonstrator has been designed and implemented to support plausible scenarios demonstrating the treatment of simulated tsunami threats with an essential subset of a National Tsunami Warning Centre (NTWC). The feasibility and the potentials of the implemented approach are demonstrated covering standard operations as well as tsunami detection and alerting functions. The demonstrator presented addresses information management and decision-support processes in a hypothetical natural crisis situation caused by a tsunami in the Eastern Mediterranean. Developments of the system are based to the largest extent on free and open source software (FOSS) components and industry standards. Emphasis has been and will be made on leveraging open source technologies that support mature system architecture models wherever appropriate. All open source software produced is foreseen to be published on a publicly available software repository thus allowing others to reuse results achieved and enabling further development and collaboration with a wide community including scientists, developers, users and stakeholders. This live demonstration is linked with the talk "TRIDEC Natural Crisis Management Demonstrator for Tsunamis" (EGU2012-7275) given in the session "Architecture of Future Tsunami Warning Systems" (NH5.7/ESSI1.7).

Organizing Schools to Address Early Warning Indicators (EWIs): Common Practices and Challenges

ERIC Educational Resources Information Center

Davis, Marcia; Herzog, Liza; Legters, Nettie

2013-01-01

An early warning system is an intentional process whereby school personnel collectively analyze student data to monitor students at risk of falling off track for graduation and to provide the interventions and resources to intervene. We studied the process of monitoring the early warning indicators and implementing interventions to ascertain…

78 FR 78321 - Early Warning Reporting, Foreign Defect Reporting, and Motor Vehicle and Equipment Recall...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... DEPARTMENT OF TRANSPORTATION National Highway Traffic Safety Administration 49 CFR Parts 573, 577, and 579 [Docket No. NHTSA--2012-0068; Notice 3] RIN 2127-AK72 Early Warning Reporting, Foreign Defect... final rule. Id. Manufacturers with early warning reporting (EWR) accounts may obtain a copy of the VIN...

Looming auditory collision warnings for driving.

PubMed

Gray, Rob

2011-02-01

A driving simulator was used to compare the effectiveness of increasing intensity (looming) auditory warning signals with other types of auditory warnings. Auditory warnings have been shown to speed driver reaction time in rear-end collision situations; however, it is not clear which type of signal is the most effective. Although verbal and symbolic (e.g., a car horn) warnings have faster response times than abstract warnings, they often lead to more response errors. Participants (N=20) experienced four nonlooming auditory warnings (constant intensity, pulsed, ramped, and car horn), three looming auditory warnings ("veridical," "early," and "late"), and a no-warning condition. In 80% of the trials, warnings were activated when a critical response was required, and in 20% of the trials, the warnings were false alarms. For the early (late) looming warnings, the rate of change of intensity signaled a time to collision (TTC) that was shorter (longer) than the actual TTC. Veridical looming and car horn warnings had significantly faster brake reaction times (BRT) compared with the other nonlooming warnings (by 80 to 160 ms). However, the number of braking responses in false alarm conditions was significantly greater for the car horn. BRT increased significantly and systematically as the TTC signaled by the looming warning was changed from early to veridical to late. Looming auditory warnings produce the best combination of response speed and accuracy. The results indicate that looming auditory warnings can be used to effectively warn a driver about an impending collision.

Integrating TWES and Satellite-based remote sensing: Lessons learned from the Honshu 2011 Tsunami

NASA Astrophysics Data System (ADS)

Löwe, Peter; Wächter, Joachim

2013-04-01

The Boxing Day Tsunami killed 240,000 people and inundated the affected shorelines with waves reaching heights up to 30m. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Honshu 2011 tsunami demonstrate that the key challenge for TEWS research still lies in the timely issuing of reliable early warning messages to areas at risk, but also to other stakeholders professionally involved in the unfolding event. Until now remote sensing products for Tsunami events, including crisis maps and change detection products, are exclusively linked to those phases of the disaster life cycle, which follow after the early warning stage: Response, recovery and mitigation. The International Charter for Space and Major Disasters has been initiated by the European Space Agency (ESA) and the Centre National d'Etudes Spatiales (CNES) in 1999. It coordinates a voluntary group of governmental space agencies and industry partners, to provide rapid crisis imaging and mapping to disaster and relief organisations to mitigate the effects of disasters on human life, property and the environment. The efficiency of this approach has been demonstrated in the field of Tsunami early warning by Charter activations following the Boxing Day Tsunami 2004, the Chile Tsunami 2010 and the Honshu Tsunami 2011. Traditional single-satellite operations allow at best bimonthly repeat rates over a given Area of Interest (AOI). This allows a lot of time for image acquisition campaign planning between imaging windows for the same AOI. The advent of constellations of identical remote sensing satellites in the early 21st century resulted both in daily AOI revisit capabilities and drastically reduced time frames for acquisition planning. However, the image acquisition planning for optical remote sensing satellite constellations is constrained by orbital and communication requirements: Defined time slots exist to commandeer the tasking of image acquisitions. If such a time slot has been missed, another attempt to image an AOI again can only be attempted ca. 24 hours later, due to the sun-synchronous satellite orbits Therefore it is critical to establish automated Disaster Early Warning dissemination services for the remote sensing community, to supply them with the timeliest opportunity to trigger the tasking process for the affected AOI. For very large events like a Tsunami in the Pacific, this approach provides the chance to gain additional pre-disaster imagery as a reference for change detection. In the case of the Tohoku earthquake, an ad-hoc warning dissemination process was manually dispatched by the Centre for Geoinformation Technology (CeGIT) at the German Research Centre for Geoscience, contacting RapidEye AG, once the severity of the earthquake event had been confirmed by the GEOFON geoseismic network. RapidEye AG decided to launch an imaging campaign which yielded 78 georectified image tiles (L3A) of Honshu island during the next imaging window. Of these, 26 tiles cover the affected coastline, resulting in 16,250km² of content for crisis mapping effort such as the Humanitarian Open Street Map (OSM) Team. This data was made available by RapidEye as a part of the Charter Activiation requested by Japan on March 11 2011. [1] Hoja, D., Schwinger, M.,Wendleder A.,Löwe, P., Konstanski, H., Weichelt, H.: Optimised Near-Real Time Data Acquisition for Disaster Related Rapid Mapping

Validation of a Pediatric Early Warning Score in Hospitalized Pediatric Oncology and Hematopoietic Stem Cell Transplant Patients.

PubMed

Agulnik, Asya; Forbes, Peter W; Stenquist, Nicole; Rodriguez-Galindo, Carlos; Kleinman, Monica

2016-04-01

To evaluate the correlation of a Pediatric Early Warning Score with unplanned transfer to the PICU in hospitalized oncology and hematopoietic stem cell transplant patients. We performed a retrospective matched case-control study, comparing the highest documented Pediatric Early Warning Score within 24 hours prior to unplanned PICU transfers in hospitalized pediatric oncology and hematopoietic stem cell transplant patients between September 2011 and December 2013. Controls were patients who remained on the inpatient unit and were matched 2:1 using age, condition (oncology vs hematopoietic stem cell transplant), and length of hospital stay. Pediatric Early Warning Scores were documented by nursing staff at least every 4 hours as part of routine care. Need for transfer was determined by a PICU physician called to evaluate the patient. A large tertiary/quaternary free-standing academic children's hospital. One hundred ten hospitalized pediatric oncology patients (42 oncology, 68 hematopoietic stem cell transplant) requiring unplanned PICU transfer and 220 matched controls. None. Using the highest score in the 24 hours prior to transfer for cases and a matched time period for controls, the Pediatric Early Warning Score was highly correlated with the need for PICU transfer overall (area under the receiver operating characteristic = 0.96), and in the oncology and hematopoietic stem cell transplant groups individually (area under the receiver operating characteristic = 0.95 and 0.96, respectively). The difference in Pediatric Early Warning Score results between the cases and controls was noted as early as 24 hours prior to PICU admission. Seventeen patients died (15.4%). Patients with higher Pediatric Early Warning Scores prior to transfer had increased PICU mortality (p = 0.028) and length of stay (p = 0.004). We demonstrate that our institution's Pediatric Early Warning Score is highly correlated with the need for unplanned PICU transfer in hospitalized oncology and hematopoietic stem cell transplant patients. Furthermore, we found an association between higher scores and PICU mortality. This is the first validation of a Pediatric Early Warning Score specific to the pediatric oncology and hematopoietic stem cell transplant populations, and supports the use of Pediatric Early Warning Scores as a method of early identification of clinical deterioration in this high-risk population.

The Self-Organising Seismic Early Warning Information Network

NASA Astrophysics Data System (ADS)

Kühnlenz, F.; Eveslage, I.; Fischer, J.; Fleming, K. M.; Lichtblau, B.; Milkereit, C.; Picozzi, M.

2009-12-01

The Self-Organising Seismic Early Warning Information Network (SOSEWIN) represents a new approach for Earthquake Early Warning Systems (EEWS), consisting in taking advantage of novel wireless communications technologies without the need of a planned, centralised infrastructure. It also sets out to overcome problems of insufficient node density, which typically affects present existing early warning systems, by having the SOSEWIN seismological sensing units being comprised of low-cost components (generally bought "off-the-shelf"), with each unit initially costing 100's of Euros, in contrast to 1,000's to 10,000's for standard seismological stations. The reduced sensitivity of the new sensing units arising from the use of lower-cost components will be compensated by the network's density, which in the future is expected to number 100's to 1000's over areas served currently by the order of 10's of standard stations. The robustness, independence of infrastructure, spontaneous extensibility due to a self-healing/self-organizing character in the case of removing/failing or adding sensors makes SOSEWIN potentially useful for various use cases, e.g. monitoring of building structures or seismic microzonation. Nevertheless its main purpose is the earthquake early warning, for which reason the ground motion is continuously monitored by conventional accelerometers (3-component) and processed within a station. Based on this, the network itself decides whether an event is detected through cooperating stations. SEEDLink is used to store and provide access to the sensor data. Experiences and selected experiment results with the SOSEWIN-prototype installation in the Ataköy district of Istanbul (Turkey) are presented. SOSEWIN considers also the needs of earthquake task forces, which want to set-up a temporary seismic network rapidly and with light-weighted stations to record after-shocks. The wireless and self-organising character of this sensor network is of great value to do this job in a shorter time and with less manpower compared to using common seismic stations as we could see during the L'Aquila earthquake, where SOSEWIN was used to monitor damaged buildings. We present here the graphical front-end of SOSEWIN in its usage for different scenarios. It belongs to a management infrastructure based on GIS and database technologies and therefore coupling with existing infrastructures should be simplified. Connecting the domain expert’s laptop running the management software with a SOSEWIN may be fulfilled via any arbitrary node in the network (on-site access) or via a gateway node from a remote location using the internet. The scenarios focus on the needs of certain domain experts (seismologists or maybe engineers) and include the planning of a network installation, support during the installation process and testing of this installation. Another scenario mentions monitoring aspects of an already installed SOSEWIN and finally a scenario deals with the visualization of the alarming protocol detecting an earthquake event and issuing an early warning.

Exploring the Role of Social Memory of Floods for Designing Flood Early Warning Operations

NASA Astrophysics Data System (ADS)

Girons Lopez, Marc; Di Baldassarre, Giuliano; Grabs, Thomas; Halldin, Sven; Seibert, Jan

2016-04-01

Early warning systems are an important tool for natural disaster mitigation practices, especially for flooding events. Warnings rely on near-future forecasts to provide time to take preventive actions before a flood occurs, thus reducing potential losses. However, on top of the technical capacities, successful warnings require an efficient coordination and communication among a range of different actors and stakeholders. The complexity of integrating the technical and social spheres of warning systems has, however, resulted in system designs neglecting a number of important aspects such as social awareness of floods thus leading to suboptimal results. A better understanding of the interactions and feedbacks among the different elements of early warning systems is therefore needed to improve their efficiency and therefore social resilience. When designing an early warning system two important decisions need to be made regarding (i) the hazard magnitude at and from which a warning should be issued and (ii) the degree of confidence required for issuing a warning. The first decision is usually taken based on the social vulnerability and climatic variability while the second one is related to the performance (i.e. accuracy) of the forecasting tools. Consequently, by estimating the vulnerability and the accuracy of the forecasts, these two variables can be optimized to minimize the costs and losses. Important parameters with a strong influence on the efficiency of warning systems such as social awareness are however not considered in their design. In this study we present a theoretical exploration of the impact of social awareness on the design of early warning systems. For this purpose we use a definition of social memory of flood events as a proxy for flood risk awareness and test its effect on the optimization of the warning system design variables. Understanding the impact of social awareness on warning system design is important to make more robust warnings that can better adapt to different social settings and more efficiently reduce vulnerability.

The Self-Organising Seismic Early Warning Information Network: Scenarios

NASA Astrophysics Data System (ADS)

Kühnlenz, F.; Fischer, J.; Eveslage, I.

2009-04-01

SAFER and EDIM working groups, the Department of Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany, and Section 2.1 Earthquake Risk and Early Warning, GFZ German Research Centre for Geosciences, Germany Contact: Frank Kühnlenz, kuehnlenz@informatik.hu-berlin.de The Self-Organising Seismic Early Warning Information Network (SOSEWIN) represents a new approach for Earthquake Early Warning Systems (EEWS), consisting in taking advantage of novel wireless communications technologies without the need of a planned, centralised infrastructure. It also sets out to overcome problems of insufficient node density, which typically affects present existing early warning systems, by having the SOSEWIN seismological sensing units being comprised of low-cost components (generally bought "off-the-shelf"), with each unit initially costing 100's of Euros, in contrast to 1,000's to 10,000's for standard seismological stations. The reduced sensitivity of the new sensing units arising from the use of lower-cost components will be compensated by the network's density, which in the future is expected to number 100's to 1000's over areas served currently by the order of 10's of standard stations. The robustness, independence of infrastructure, spontaneous extensibility due to a self-healing/self-organizing character in the case of removing/failing or adding sensors makes SOSEWIN potentially useful for various use cases, e.g. monitoring of building structures or seismic microzonation. Nevertheless its main purpose is the earthquake early warning, for which reason the ground motion is continuously monitored by conventional accelerometers (3-component). It uses SEEDLink to store and provide access to the sensor data. SOSEWIN considers also the needs of earthquake task forces, which want to set-up a temporary seismic network rapidly and with light-weighted stations to record after-shocks. The wireless and self-organising character of this sensor network should be of great value to do this job in a shorter time and with less manpower compared to using common seismic stations. We present here the graphical front-end of SOSEWIN in its usage for different scenarios. It belongs to a management infrastructure based on GIS and database technologies and therefore coupling with existing infrastructures should be simplified. Connecting the domain expert's laptop running the management software with a SOSEWIN may be fulfilled via any arbitrary node in the network (on-site access) or via a gateway node from a remote location using the internet. The scenarios focus on the needs of certain domain experts (seismologists or maybe engineers) and include the planning of a network installation, support during the installation process and testing of this installation. Another scenario mentions monitoring aspects of an already installed network and finally a scenario deals with the visualization of the alarming protocol detecting an earthquake event and issuing an early warning.

28 CFR 36.407 - Temporary suspension of certain detectable warning requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... detectable warning requirements. 36.407 Section 36.407 Judicial Administration DEPARTMENT OF JUSTICE... and Alterations § 36.407 Temporary suspension of certain detectable warning requirements. The detectable warning requirements contained in sections 4.7.7, 4.29.5, and 4.29.6 of appendix A to this part...

Managing Risks? Early Warning Systems for Climate Change

NASA Astrophysics Data System (ADS)

Sitati, A. M.; Zommers, Z. A.; Habilov, M.

2014-12-01

Early warning systems are a tool with which to minimize risks posed by climate related hazards. Although great strides have been made in developing early warning systems most deal with one hazard, only provide short-term warnings and do not reach the most vulnerable. This presentation will review research results of the United Nations Environment Programme's CLIM-WARN project. The project seeks to identify how governments can better communicate risks by designing multi-hazard early warning systems that deliver actionable warnings across timescales. Household surveys and focus group discussions were conducted in 36 communities in Kenya, Ghana and Burkina Faso in order to identify relevant climate related hazards, current response strategies and early warning needs. Preliminary results show significant variability in both risks and needs within and between countries. For instance, floods are more frequent in rural western parts of Kenya. Droughts are frequent in the north while populations in urban areas face a range of hazards - floods, droughts, disease outbreaks - that sometimes occur simultaneously. The majority of the rural population, especially women, the disabled and the elderly, do not have access to modern media such as radio, television, or internet. While 55% of rural populace never watches television, 64% of urban respondents watch television on a daily basis. Communities have different concepts of how to design warning systems. It will be a challenge for national governments to create systems that accommodate such diversity yet provide standard quality of service to all. There is a need for flexible and forward-looking early warning systems that deliver broader information about risks. Information disseminated through the system could not only include details of hazards, but also long-term adaptation options, general education, and health information, thus increasingly both capabilities and response options.

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

Hybrid Intrusion Forecasting Framework for Early Warning System

NASA Astrophysics Data System (ADS)

Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip

2011-01-01

U.S. forests occupy approx. 751 million acres (approx. 1/3 of total land). These forests are exposed to multiple biotic and abiotic threats that collectively damage extensive acreages each year. Hazardous forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest monitoring products are needed to aid forest management and decision making by the US Forest Service and its state and private partners. Daily MODIS data products provide a means to monitor regional forest disturbances on a weekly basis. In response, we began work in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat early warning system (EWS)

A new real-time tsunami detection algorithm

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Pignagnoli, L.

2016-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection based on the real-time tide removal and real-time band-pass filtering of sea-bed pressure recordings. The algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability, at low computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. Pressure data sets acquired by Bottom Pressure Recorders in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event which occurred at Haida Gwaii on October 28th, 2012 using data recorded by the Bullseye underwater node of Ocean Networks Canada. The algorithm successfully ran for test purpose in year-long missions onboard the GEOSTAR stand-alone multidisciplinary abyssal observatory, deployed in the Gulf of Cadiz during the EC project NEAREST and on NEMO-SN1 cabled observatory deployed in the Western Ionian Sea, operational node of the European research infrastructure EMSO.

Prototype early warning system for heart disease detection using Android Application.

PubMed

Zennifa, Fadilla; Fitrilina; Kamil, Husnil; Iramina, Keiji

2014-01-01

Heart Disease affects approximately 70 million people worldwide where most people do not even know the symptoms. This research examines the prototype of early warning system for heart disease by android application. It aims to facilitate users to early detect heart disease which can be used independently. To build the application in android phone, variable centered intelligence rule system (VCIRS) as decision makers and pulse sensor - Arduino as heart rate detector were applied in this study. Moreover, in Arduino, the heart rate will become an input for symptoms in Android Application. The output of this system is the conclusion statement of users diagnosed with either coronary heart disease, hypertension heart disease, rheumatic heart disease or do not get any kind of heart disease. The result of diagnosis followed by analysis of the value of usage variable rate (VUR) rule usage rate (RUR) and node usage rate (NUR) that shows the value of the rule that will increase when the symptoms frequently appear. This application was compared with the medical analysis from 35 cases of heart disease and it showed concordance between diagnosis from android application and expert diagnosis of the doctors.

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, J.; Norman, S. P.

2013-12-01

Forest threats across the US have become increasingly evident in recent years. These include regionally extensive disturbances (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and result in extensive forest mortality. In addition, forests can be subject to ephemeral, sometimes yearly defoliation from various insects and types of storm damage. After prolonged severe disturbance, signs of forest recovery can vary in terms of satellite-based Normalized Difference Vegetation Index (NDVI) values. The increased extent and threat of forest disturbances in part led to the enactment of the 2003 Healthy Forest Restoration Act, which mandated that a national forest threat Early Warning System (EWS) be deployed. In response, the US Forest Service collaborated with NASA, DOE Oak Ridge National Laboratory, and the USGS Eros Data Center to build the near real time ForWarn forest threat EWS for monitoring regionally evident forest disturbances, starting on-line operations in 2010. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines used with current NDVI to derive a suite of six nationwide 'weekly' forest change products. ForWarn uses daily 232 meter MODIS Aqua and Terra satellite NDVI data, including MOD13 products for deriving historical baseline NDVIs and eMODIS products for compiling current NDVI. Separately pre-processing the current and historical NDVIs, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally reduce noise, fuse, and aggregate MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of forest change products per year. The 24 day compositing interval typically enables new disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. ForWarn's three standard forest change products compare current NDVI to that from the previous year, previous 3 years, and all previous years since 2000. Other forest change products added in 2013 include one for quicker disturbance detection and two others that adjust for seasonal fluctuations in normal vegetation phenology. This product suite and ForWarn's geospatial data viewer allow end users to view and assess disturbance dynamics for many regionally evident biotic and abiotic forest disturbances throughout a given current year. ForWarn's change products are also being used for forest change trend analysis and for developing regional forest overstory mortality products. They are used to alert forest health specialists about new regional forest disturbances. Such alerts also typically consider available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances for multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn provides forest change products that could be combined with other geospatial data on forest biomass to help assess forest disturbance carbon impacts within the conterminous US.

The pathway to earthquake early warning in the US

NASA Astrophysics Data System (ADS)

Allen, R. M.; Given, D. D.; Heaton, T. H.; Vidale, J. E.; West Coast Earthquake Early Warning Development Team

2013-05-01

The development of earthquake early warning capabilities in the United States is now accelerating and expanding as the technical capability to provide warning is demonstrated and additional funding resources are making it possible to expand the current testing region to the entire west coast (California, Oregon and Washington). Over the course of the next two years we plan to build a prototype system that will provide a blueprint for a full public system in the US. California currently has a demonstrations warning system, ShakeAlert, that provides alerts to a group of test users from the public and private sector. These include biotech companies, technology companies, the entertainment industry, the transportation sector, and the emergency planning and response community. Most groups are currently in an evaluation mode, receiving the alerts and developing protocols for future response. The Bay Area Rapid Transit (BART) system is the one group who has now implemented an automated response to the warning system. BART now stops trains when an earthquake of sufficient size is detected. Research and development also continues to develop improved early warning algorithms to better predict the distribution of shaking in large earthquakes when the finiteness of the source becomes important. The algorithms under development include the use of both seismic and GPS instrumentation and integration with existing point source algorithms. At the same time, initial testing and development of algorithms in and for the Pacific Northwest is underway. In this presentation we will review the current status of the systems, highlight the new research developments, and lay out a pathway to a full public system for the US west coast. The research and development described is ongoing at Caltech, UC Berkeley, University of Washington, ETH Zurich, Southern California Earthquake Center, and the US Geological Survey, and is funded by the Gordon and Betty Moore Foundation and the US Geological Survey.

Early Warning Program to Detect and Identify Contaminants of Emerging Concern and Their Effects to Fish and Wildlife

EPA Science Inventory

The Great Lakes basin provides an opportunity to investigate impacts to fish and wildlife from various natural and anthropogenic influences, particularly within Areas of Concern (AOC). While AOC beneficial use impairments related to chemical pollution largely encompass legacy con...

A Forehead-Mounted Measure of O2 Saturation: The Potential for in Cockpit Hypoxia Early Detection and Warning

DTIC Science & Technology

2010-07-09

past 24 hours. (circle all that apply) a. None b. Sedatives/Tranquilizers c. Aspirin/ Tylenol /any analgesic d. Antihistamines...e. Decongestants f. Other (please specify) 6. Do you take any over the counter medications (e.g., antacids, Benadryl, Tylenol , etc

Landslide risk mitigation by means of early warning systems

NASA Astrophysics Data System (ADS)

Calvello, Michele

2017-04-01

Among the many options available to mitigate landslide risk, early warning systems may be used where, in specific circumstances, the risk to life increases above tolerable levels. A coherent framework to classify and analyse landslide early warning systems (LEWS) is herein presented. Once the objectives of an early warning strategy are defined depending on the scale of analysis and the type of landslides to address, the process of designing and managing a LEWS should synergically employ technical and social skills. A classification scheme for the main components of LEWSs is proposed for weather-induced landslides. The scheme is based on a clear distinction among: i) the landslide model, i.e. a functional relationship between weather characteristics and landslide events considering the geotechnical, geomorphological and hydro-geological characterization of the area as well as an adequate monitoring strategy; ii) the warning model, i.e. the landslide model plus procedures to define the warning events and to issue the warnings; iii) the warning system, i.e. the warning model plus warning dissemination procedures, communication and education tools, strategies for community involvement and emergency plans. Each component of a LEWS is related to a number of actors involved with their deployment, operational activities and management. For instance, communication and education, community involvement and emergency plans are all significantly influenced by people's risk perception and by operational aspects system managers need to address in cooperation with scientists.

Accuracy of a pediatric early warning score in the recognition of clinical deterioration.

PubMed

Miranda, Juliana de Oliveira Freitas; Camargo, Climene Laura de; Nascimento, Carlito Lopes; Portela, Daniel Sales; Monaghan, Alan

2017-07-10

to evaluate the accuracy of the version of the Brighton Pediatric Early Warning Score translated and adapted for the Brazilian context, in the recognition of clinical deterioration. a diagnostic test study to measure the accuracy of the Brighton Pediatric Early Warning Score for the Brazilian context, in relation to a reference standard. The sample consisted of 271 children, aged 0 to 10 years, blindly evaluated by a nurse and a physician, specialists in pediatrics, with interval of 5 to 10 minutes between the evaluations, for the application of the Brighton Pediatric Early Warning Score for the Brazilian context and of the reference standard. The data were processed and analyzed using the Statistical Package for the Social Sciences and VassarStats.net programs. The performance of the Brighton Pediatric Early Warning Score for the Brazilian context was evaluated through the indicators of sensitivity, specificity, predictive values, area under the ROC curve, likelihood ratios and post-test probability. the Brighton Pediatric Early Warning Score for the Brazilian context showed sensitivity of 73.9%, specificity of 95.5%, positive predictive value of 73.3%, negative predictive value of 94.7%, area under Receiver Operating Characteristic Curve of 91.9% and the positive post-test probability was 80%. the Brighton Pediatric Early Warning Score for the Brazilian context, presented good performance, considered valid for the recognition of clinical deterioration warning signs of the children studied. avaliar a acurácia da versão traduzida e adaptada do Brighton Paediatric Early Warning Score para o contexto brasileiro, no reconhecimento da deterioração clínica. estudo de teste diagnóstico para medir a acurácia do Brighton Paediatric Early Warning Score, para o contexto brasileiro, em relação a um padrão de referência. A amostra foi composta por 271 crianças de 0 a 10 anos, avaliadas de forma cega por uma enfermeira e um médico, especialistas em pediatria, com intervalo de 5 a 10 minutos entre as avaliações, para aplicação do Brighton Paediatric Early Warning Score, para o contexto brasileiro e do padrão de referência. Os dados foram processados e analisados nos programas Statistical Package for the Social Sciences e VassarStats.net. O desempenho do Brighton Paediatric Early Warning Score para o contexto brasileiro foi avaliado por meio dos indicadores de sensibilidade, especificidade, valores preditivos, área sob a curva ROC, razões de probabilidades e probabilidade pós-teste. o Brighton Paediatric Early Warning Score para o contexto brasileiro apresentou sensibilidade de 73,9%, especificidade de 95,5%, valor preditivo positivo de 73,3%, valor preditivo negativo de 94,7%, área sob a Receiver Operating Characteristic Curve de 91,9% e a probabilidade pós-teste positivo foi de 80%. o Brighton Paediatric Early Warning Score, para o contexto brasileiro, apresentou bom desempenho, considerado válido para o reconhecimento de sinais de alerta de deterioração clínica das crianças estudadas. evaluar la precisión de la versión traducida y adaptada del Brighton Paediatric Early Warning Score para el contexto brasileño, en el reconocimiento de la deterioración clínica. estudio de test diagnóstico para medir la precisión del Brighton Paediatric Early Warning Score para el contexto brasileño, en relación a un estándar de referencia. La muestra estuvo compuesta por 271 niños de 0 a 10 años, evaluadas de forma ciega por especialistas en pediatría, una enfermera y un médico, con intervalo de 5 a 10 minutos entre las evaluaciones, para aplicación del Brighton Paediatric Early Warning Score para el contexto brasileño. Los datos fueron procesados y analizados en los programas Statistical Package for the Social Sciences y VassarStats.net. El desempeño del Brighton Paediatric Early Warning Score para el contexto brasileño fue evaluado por medio de los indicadores de sensibilidad, especificidad, valores predictivos, área debajo de la curva ROC, razones de probabilidades y probabilidad postest. el Brighton Paediatric Early Warning Score para el contexto brasileño presentó sensibilidad de 73,9%, especificidad de 95,5%, valor predictivo positivo de 73,3%, valor predictivo negativo de 94,7%, área bajo la Receiver Operating Characteristic Curve de 91,9% y la probabilidad postest positivo fue de 80%. el Brighton Paediatric Early Warning Score para el contexto brasileño, presentó buen desempeño, considerado válido para el reconocimiento de señales de alerta de deterioración clínica de los niños estudiados.

A national survey of obstetric early warning systems in the United Kingdom: five years on.

PubMed

Isaacs, R A; Wee, M Y K; Bick, D E; Beake, S; Sheppard, Z A; Thomas, S; Hundley, V; Smith, G B; van Teijlingen, E; Thomas, P W

2014-07-01

The Confidential Enquiries into Maternal Deaths in the UK have recommended obstetric early warning systems for early identification of clinical deterioration to reduce maternal morbidity and mortality. This survey explored early warning systems currently used by maternity units in the UK. An electronic questionnaire was sent to all 205 lead obstetric anaesthetists under the auspices of the Obstetric Anaesthetists' Association, generating 130 (63%) responses. All respondents reported use of an obstetric early warning system, compared with 19% in a similar survey in 2007. Respondents agreed that the six most important physiological parameters to record were respiratory rate, heart rate, temperature, systolic and diastolic blood pressure and oxygen saturation. One hundred and eighteen (91%) lead anaesthetists agreed that early warning systems helped to prevent obstetric morbidity. Staffing pressures were perceived as the greatest barrier to their use, and improved audit, education and training for healthcare professionals were identified as priority areas. © 2014 The Association of Anaesthetists of Great Britain and Ireland.

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication

PubMed Central

Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A.; Aylward, R. Bruce; Grassly, Nicholas C.

2016-01-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities. PMID:26890053

Faster Detection of Poliomyelitis Outbreaks to Support Polio Eradication.

PubMed

Blake, Isobel M; Chenoweth, Paul; Okayasu, Hiro; Donnelly, Christl A; Aylward, R Bruce; Grassly, Nicholas C

2016-03-01

As the global eradication of poliomyelitis approaches the final stages, prompt detection of new outbreaks is critical to enable a fast and effective outbreak response. Surveillance relies on reporting of acute flaccid paralysis (AFP) cases and laboratory confirmation through isolation of poliovirus from stool. However, delayed sample collection and testing can delay outbreak detection. We investigated whether weekly testing for clusters of AFP by location and time, using the Kulldorff scan statistic, could provide an early warning for outbreaks in 20 countries. A mixed-effects regression model was used to predict background rates of nonpolio AFP at the district level. In Tajikistan and Congo, testing for AFP clusters would have resulted in an outbreak warning 39 and 11 days, respectively, before official confirmation of large outbreaks. This method has relatively high specificity and could be integrated into the current polio information system to support rapid outbreak response activities.

Limitation of the Predominant-Period Estimator for Earthquake Early Warning and the Initial Rupture of Earthquakes

NASA Astrophysics Data System (ADS)

Yamada, T.; Ide, S.

2007-12-01

Earthquake early warning is an important and challenging issue for the reduction of the seismic damage, especially for the mitigation of human suffering. One of the most important problems in earthquake early warning systems is how immediately we can estimate the final size of an earthquake after we observe the ground motion. It is relevant to the problem whether the initial rupture of an earthquake has some information associated with its final size. Nakamura (1988) developed the Urgent Earthquake Detection and Alarm System (UrEDAS). It calculates the predominant period of the P wave (τp) and estimates the magnitude of an earthquake immediately after the P wave arrival from the value of τpmax, or the maximum value of τp. The similar approach has been adapted by other earthquake alarm systems (e.g., Allen and Kanamori (2003)). To investigate the characteristic of the parameter τp and the effect of the length of the time window (TW) in the τpmax calculation, we analyze the high-frequency recordings of earthquakes at very close distances in the Mponeng mine in South Africa. We find that values of τpmax have upper and lower limits. For larger earthquakes whose source durations are longer than TW, the values of τpmax have an upper limit which depends on TW. On the other hand, the values for smaller earthquakes have a lower limit which is proportional to the sampling interval. For intermediate earthquakes, the values of τpmax are close to their typical source durations. These two limits and the slope for intermediate earthquakes yield an artificial final size dependence of τpmax in a wide size range. The parameter τpmax is useful for detecting large earthquakes and broadcasting earthquake early warnings. However, its dependence on the final size of earthquakes does not suggest that the earthquake rupture is deterministic. This is because τpmax does not always have a direct relation to the physical quantities of an earthquake.

Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

2015-06-30

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik F.; Marianno, Fernando J.

2015-12-22

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

Floods in 2002 and 2013: comparing flood warnings and emergency measures from the perspective of affected parties

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Pech, Ina; Schröter, Kai; Müller, Meike; Thieken, Annegret

2016-04-01

Early warning is essential for protecting people and mitigating damage in case of flood events. However, early warning is only helpful if the flood-endangered parties are reached by the warning and if they know how to react effectively. Finding suitable methods for communicating helpful warnings to the "last mile" remains a challenge, but not much information is available. Surveys were undertaken after the August 2002 and the June 2013 floods in Germany, asking affected private households and companies about warnings they received and emergency measures they undertook. Results show, that in 2002 early warning did not work well: in too many areas warnings came too late or were too imprecise and many people (27%) and companies (45%) did not receive a flood warning. Afterwards, the warning systems were significantly improved, so that in 2013 only a small share of the affected people (7%) and companies (7 %) was not reached by any warning. Additionally, private households and companies were hardly aware of the flood risk in the Elbe catchment before 2002, mainly due to a lack of flood experience. For instance, in 2002 only 14% of private households clearly knew how to protect themselves and their assets when the warning reached them, in 2013 this fraction was 46 %. Although the share of companies which had an emergency plan in place had increased from 10 % in 2002 to 26 % in 2013, and the share of those conducting regular emergency exercises had increased from 4 % to 13 %, there is still plenty of room for improvement. Therefore, integrated early warning systems from monitoring through to the reaction of the affected parties as well as effective risk and emergency communication need continuous further improvement to protect people and mitigate residual risks in case of floods.

Performances of the New Real Time Tsunami Detection Algorithm applied to tide gauges data

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Morucci, S.

2017-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection (TDA) based on the real-time tide removal and real-time band-pass filtering of seabed pressure time series acquired by Bottom Pressure Recorders. The TDA algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. In this work we present the performance of the TDA algorithm applied to tide gauge data. We have adapted the new tsunami detection algorithm and the Monte Carlo test methodology to tide gauges. Sea level data acquired by coastal tide gauges in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event generated by Tohoku earthquake on March 11th 2011, using data recorded by several tide gauges scattered all over the Pacific area.

Expert system for online surveillance of nuclear reactor coolant pumps

DOEpatents

Gross, Kenny C.; Singer, Ralph M.; Humenik, Keith E.

1993-01-01

An expert system for online surveillance of nuclear reactor coolant pumps. This system provides a means for early detection of pump or sensor degradation. Degradation is determined through the use of a statistical analysis technique, sequential probability ratio test, applied to information from several sensors which are responsive to differing physical parameters. The results of sequential testing of the data provide the operator with an early warning of possible sensor or pump failure.

Neonatal Early Warning Tools for recognising and responding to clinical deterioration in neonates cared for in the maternity setting: A retrospective case-control study.

PubMed

Paliwoda, Michelle; New, Karen; Bogossian, Fiona

2016-09-01

All newborns are at risk of deterioration as a result of failing to make the transition to extra uterine life. Signs of deterioration can be subtle and easily missed. It has been postulated that the use of an Early Warning Tool may assist clinicians in recognising and responding to signs of deterioration earlier in neonates, thereby preventing a serious adverse event. To examine whether observations from a Standard Observation Tool, applied to three neonatal Early Warning Tools, would hypothetically trigger an escalation of care more frequently than actual escalation of care using the Standard Observation Tool. A retrospective case-control study. A maternity unit in a tertiary public hospital in Australia. Neonates born in 2013 of greater than or equal to 34(+0) weeks gestation, admitted directly to the maternity ward from their birthing location and whose subsequent deterioration required admission to the neonatal unit, were identified as cases from databases of the study hospital. Each case was matched with three controls, inborn during the same period and who did not experience deterioration and neonatal unit admission. Clinical and physiological data recorded on a Standard Observation Tool, from time of admission to the maternity ward, for cases and controls were charted onto each of three Early Warning Tools. The primary outcome was whether the tool 'triggered an escalation of care'. Descriptive statistics (n, %, Mean and SD) were employed. Cases (n=26) comprised late preterm, early term and post-term neonates and matched by gestational age group with 3 controls (n=78). Overall, the Standard Observation Tool triggered an escalation of care for 92.3% of cases compared to the Early Warning Tools; New South Wales Health 80.8%, United Kingdom Newborn Early Warning Chart 57.7% and The Australian Capital Territory Neonatal Early Warning Score 11.5%. Subgroup analysis by gestational age found differences between the tools in hypothetically triggering an escalation of care. The Standard Observation Tool triggered an escalation of care more frequently than the Early Warning Tools, which may be as a result of behavioural data captured on the Standard Observation Tool and escalated, which could not be on the Early Warning Tools. Findings demonstrate that a single tool applied to all gestational age ranges may not be effective in identifying early deterioration or may over trigger an escalation of care. Further research is required into the sensitivity and specificity of Early Warning Tools in neonatal sub-populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition

PubMed Central

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA – a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. PMID:24367574

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition.

PubMed

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

[Health threats and health system crises. An approach to early warning and response. 2008 SESPAS Report].

PubMed

Simón Soria, Fernando; Guillén Enríquez, Francisco Javier

2008-04-01

The world is changing more and faster than ever before. New diseases are coming to light each year, controlled diseases are reemerging as potential threats, and natural or man-made disasters are increasingly affecting human health. The "International Health Regulations (2005)" reflect the changes in the response of public health to this new situation. Surveillance of specific diseases and predefined control measures have been replaced by surveillance of public health events of international concern and control measures adapted to each situation. The public health events of international interest are characterized by their seriousness, predictability, the risk of international spread and potential for travel or trade restrictions. The development of the European Early Warning and Response System in 1998 and the creation of the European Center for Disease Prevention and Control in 2005 demonstrate political commitment in Europe, with early detection of and response to public health threats. However, timely risk evaluation and response at a national level requires improved data digitalization and accessibility, automatic notification processes, data analysis and dissemination of information, the combination of information from multiple sources and adaptation of public health services. The autonomous regions in Spain are initiating this adaptation process, but interoperability between systems and the development of guidelines for a coordinated response should be steered by the National Interregional Health Council and coordinated by the Ministry of Health. Efficient early warning systems of health threats that allow for a timely response and reduce uncertainty about information would help to minimize the risk of public health crises. The profile of public health threats is nonspecific. Early detection of threats requires access to information from multiple sources and efficient risk assessment. Key factors for improving the response to public health threats are the development of surveillance methods and operational research in public health.

Detection of solar events

DOEpatents

Fischbach, Ephraim; Jenkins, Jere

2013-08-27

A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

Detection of neutrinos

DOEpatents

Fischbach, Ephraim; Jenkins, Jere

2016-05-10

A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

Determining the Orbit Locations of Turkish Airborne Early Warning and Control Aircraft Over the Turkish Air Space

DTIC Science & Technology

2009-03-01

and Control (AEW&C) Aircraft. AEW&C aircraft has become vital to detect low altitude threats that a ground RADAR cannot detect because of obstacles...HARM). The concern is to cover and detect the threats as far as possible from Turkey within a risk that the commander accepts. The goal is to help...decision makers decide how many AEW aircraft are needed to obtain full coverage. In order to provide optimum results, a Maximal Coverage Location

Detection of neutrinos

DOEpatents

Fischbach, Ephraim; Jenkins, Jere

2014-02-04

A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

Web-based Tsunami Early Warning System with instant Tsunami Propagation Calculations in the GPU Cloud

NASA Astrophysics Data System (ADS)

Hammitzsch, M.; Spazier, J.; Reißland, S.

2014-12-01

Usually, tsunami early warning and mitigation systems (TWS or TEWS) are based on several software components deployed in a client-server based infrastructure. The vast majority of systems importantly include desktop-based clients with a graphical user interface (GUI) for the operators in early warning centers. However, in times of cloud computing and ubiquitous computing the use of concepts and paradigms, introduced by continuously evolving approaches in information and communications technology (ICT), have to be considered even for early warning systems (EWS). Based on the experiences and the knowledge gained in three research projects - 'German Indonesian Tsunami Early Warning System' (GITEWS), 'Distant Early Warning System' (DEWS), and 'Collaborative, Complex, and Critical Decision-Support in Evolving Crises' (TRIDEC) - new technologies are exploited to implement a cloud-based and web-based prototype to open up new prospects for EWS. This prototype, named 'TRIDEC Cloud', merges several complementary external and in-house cloud-based services into one platform for automated background computation with graphics processing units (GPU), for web-mapping of hazard specific geospatial data, and for serving relevant functionality to handle, share, and communicate threat specific information in a collaborative and distributed environment. The prototype in its current version addresses tsunami early warning and mitigation. The integration of GPU accelerated tsunami simulation computations have been an integral part of this prototype to foster early warning with on-demand tsunami predictions based on actual source parameters. However, the platform is meant for researchers around the world to make use of the cloud-based GPU computation to analyze other types of geohazards and natural hazards and react upon the computed situation picture with a web-based GUI in a web browser at remote sites. The current website is an early alpha version for demonstration purposes to give the concept a whirl and to shape science's future. Further functionality, improvements and possible profound changes have to implemented successively based on the users' evolving needs.

Anatomy of Historical Tsunamis: Lessons Learned for Tsunami Warning

NASA Astrophysics Data System (ADS)

Igarashi, Y.; Kong, L.; Yamamoto, M.; McCreery, C. S.

2011-11-01

Tsunamis are high-impact disasters that can cause death and destruction locally within a few minutes of their occurrence and across oceans hours, even up to a day, afterward. Efforts to establish tsunami warning systems to protect life and property began in the Pacific after the 1946 Aleutian Islands tsunami caused casualties in Hawaii. Seismic and sea level data were used by a central control center to evaluate tsunamigenic potential and then issue alerts and warnings. The ensuing events of 1952, 1957, and 1960 tested the new system, which continued to expand and evolve from a United States system to an international system in 1965. The Tsunami Warning System in the Pacific (ITSU) steadily improved through the decades as more stations became available in real and near-real time through better communications technology and greater bandwidth. New analysis techniques, coupled with more data of higher quality, resulted in better detection, greater solution accuracy, and more reliable warnings, but limitations still exist in constraining the source and in accurately predicting propagation of the wave from source to shore. Tsunami event data collected over the last two decades through international tsunami science surveys have led to more realistic models for source generation and inundation, and within the warning centers, real-time tsunami wave forecasting will become a reality in the near future. The tsunami warning system is an international cooperative effort amongst countries supported by global and national monitoring networks and dedicated tsunami warning centers; the research community has contributed to the system by advancing and improving its analysis tools. Lessons learned from the earliest tsunamis provided the backbone for the present system, but despite 45 years of experience, the 2004 Indian Ocean tsunami reminded us that tsunamis strike and kill everywhere, not just in the Pacific. Today, a global intergovernmental tsunami warning system is coordinated under the United Nations. This paper reviews historical tsunamis, their warning activities, and their sea level records to highlight lessons learned with the focus on how these insights have helped to drive further development of tsunami warning systems and their tsunami warning centers. While the international systems do well for teletsunamis, faster detection, more accurate evaluations, and widespread timely alerts are still the goals, and challenges still remain to achieving early warning against the more frequent and destructive local tsunamis.

Massachusetts Early Warning Indicator System (EWIS). "Technical Descriptions of Risk Model Development": Middle and High School Age Groupings (Grades 7-12)

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…

APDS: Autonomous Pathogen Detection System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langlois, R G; Brown, S; Burris, L

An early warning system to counter bioterrorism, the Autonomous Pathogen Detection System (APDS) continuously monitors the environment for the presence of biological pathogens (e.g., anthrax) and once detected, it sounds an alarm much like a smoke detector warns of a fire. Long before September 11, 2001, this system was being developed to protect domestic venues and events including performing arts centers, mass transit systems, major sporting and entertainment events, and other high profile situations in which the public is at risk of becoming a target of bioterrorist attacks. Customizing off-the-shelf components and developing new components, a multidisciplinary team developed APDS,more » a stand-alone system for rapid, continuous monitoring of multiple airborne biological threat agents in the environment. The completely automated APDS samples the air, prepares fluid samples in-line, and performs two orthogonal tests: immunoassay and nucleic acid detection. When compared to competing technologies, APDS is unprecedented in terms of flexibility and system performance.« less

Ionospheric earthquake effects detection based on Total Electron Content (TEC) GPS Correlation

NASA Astrophysics Data System (ADS)

Sunardi, Bambang; Muslim, Buldan; Eka Sakya, Andi; Rohadi, Supriyanto; Sulastri; Murjaya, Jaya

2018-03-01

Advances in science and technology showed that ground-based GPS receiver was able to detect ionospheric Total Electron Content (TEC) disturbances caused by various natural phenomena such as earthquakes. One study of Tohoku (Japan) earthquake, March 11, 2011, magnitude M 9.0 showed TEC fluctuations observed from GPS observation network spread around the disaster area. This paper discussed the ionospheric earthquake effects detection using TEC GPS data. The case studies taken were Kebumen earthquake, January 25, 2014, magnitude M 6.2, Sumba earthquake, February 12, 2016, M 6.2 and Halmahera earthquake, February 17, 2016, M 6.1. TEC-GIM (Global Ionosphere Map) correlation methods for 31 days were used to monitor TEC anomaly in ionosphere. To ensure the geomagnetic disturbances due to solar activity, we also compare with Dst index in the same time window. The results showed anomalous ratio of correlation coefficient deviation to its standard deviation upon occurrences of Kebumen and Sumba earthquake, but not detected a similar anomaly for the Halmahera earthquake. It was needed a continous monitoring of TEC GPS data to detect the earthquake effects in ionosphere. This study giving hope in strengthening the earthquake effect early warning system using TEC GPS data. The method development of continuous TEC GPS observation derived from GPS observation network that already exists in Indonesia is needed to support earthquake effects early warning systems.

Integrating Remote Sensing and Disease Surveillance to Forecast Malaria Epidemics

NASA Astrophysics Data System (ADS)

Wimberly, M. C.; Beyane, B.; DeVos, M.; Liu, Y.; Merkord, C. L.; Mihretie, A.

2015-12-01

Advance information about the timing and locations of malaria epidemics can facilitate the targeting of resources for prevention and emergency response. Early detection methods can detect incipient outbreaks by identifying deviations from expected seasonal patterns, whereas early warning approaches typically forecast future malaria risk based on lagged responses to meteorological factors. A critical limiting factor for implementing either of these approaches is the need for timely and consistent acquisition, processing and analysis of both environmental and epidemiological data. To address this need, we have developed EPIDEMIA - an integrated system for surveillance and forecasting of malaria epidemics. The EPIDEMIA system includes a public health interface for uploading and querying weekly surveillance reports as well as algorithms for automatically validating incoming data and updating the epidemiological surveillance database. The newly released EASTWeb 2.0 software application automatically downloads, processes, and summaries remotely-sensed environmental data from multiple earth science data archives. EASTWeb was implemented as a component of the EPIDEMIA system, which combines the environmental monitoring data and epidemiological surveillance data into a unified database that supports both early detection and early warning models. Dynamic linear models implemented with Kalman filtering were used to carry out forecasting and model updating. Preliminary forecasts have been disseminated to public health partners in the Amhara Region of Ethiopia and will be validated and refined as the EPIDEMIA system ingests new data. In addition to continued model development and testing, future work will involve updating the public health interface to provide a broader suite of outbreak alerts and data visualization tools that are useful to our public health partners. The EPIDEMIA system demonstrates a feasible approach to synthesizing the information from epidemiological surveillance systems and remotely-sensed environmental monitoring systems to improve malaria epidemic detection and forecasting.

Fire Detector

NASA Technical Reports Server (NTRS)

1978-01-01

An early warning fire detection sensor developed for NASA's Space Shuttle Orbiter is being evaluated as a possible hazard prevention system for mining operations. The incipient Fire Detector represents an advancement over commercially available smoke detectors in that it senses and signals the presence of a fire condition before the appearance of flame and smoke, offering an extra margin of safety.

33 CFR 83.07 - Risk of collision (Rule 7).

Code of Federal Regulations, 2011 CFR

2011-07-01

... exists. If there is any doubt such risk shall be deemed to exist. (b) Radar. Proper use shall be made of radar equipment if fitted and operational, including long-range scanning to obtain early warning of risk of collision and radar plotting or equivalent systematic observation of detected objects. (c) Scanty...

33 CFR 83.07 - Risk of collision (Rule 7).

Code of Federal Regulations, 2010 CFR

2010-07-01

... exists. If there is any doubt such risk shall be deemed to exist. (b) Radar. Proper use shall be made of radar equipment if fitted and operational, including long-range scanning to obtain early warning of risk of collision and radar plotting or equivalent systematic observation of detected objects. (c) Scanty...

77 FR 58081 - Protection of Stratospheric Ozone: Listing of Substitutes for Ozone-Depleting Substances-Fire...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-19

... protection options including new, improved technology for early warning and smoke detection. Thus, EPA is... require state, local, or tribal governments to change their regulations. Thus, Executive Order 13132 does... governments to change their regulations. Thus, Executive Order 13175 does not apply to this action. G...

Detection and early warning of WNV circulation in Central Macedonia, Greece using sentinel chickens and mosquitoes

USDA-ARS?s Scientific Manuscript database

Following West Nile Virus (WNV) epidemic in 2010 in Central Macedonia, Greece, which resulted in 197 human neuroinvasive disease cases, we determined the seasonal appearance and prevalence of the virus in 2011 by testing weekly for WNV genomic RNA in mosquitoes collected in carbon-dioxide baited tra...

33 CFR 83.07 - Risk of collision (Rule 7).

Code of Federal Regulations, 2013 CFR

2013-07-01

... exists. If there is any doubt such risk shall be deemed to exist. (b) Radar. Proper use shall be made of radar equipment if fitted and operational, including long-range scanning to obtain early warning of risk of collision and radar plotting or equivalent systematic observation of detected objects. (c) Scanty...

33 CFR 83.07 - Risk of collision (Rule 7).

Code of Federal Regulations, 2014 CFR

2014-07-01

... exists. If there is any doubt such risk shall be deemed to exist. (b) Radar. Proper use shall be made of radar equipment if fitted and operational, including long-range scanning to obtain early warning of risk of collision and radar plotting or equivalent systematic observation of detected objects. (c) Scanty...

33 CFR 83.07 - Risk of collision (Rule 7).

Code of Federal Regulations, 2012 CFR

2012-07-01

... exists. If there is any doubt such risk shall be deemed to exist. (b) Radar. Proper use shall be made of radar equipment if fitted and operational, including long-range scanning to obtain early warning of risk of collision and radar plotting or equivalent systematic observation of detected objects. (c) Scanty...

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

NASA Astrophysics Data System (ADS)

Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

2017-07-01

Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

Use of media and public-domain Internet sources for detection and assessment of plant health threats

PubMed Central

Thomas, Carla S.; Nelson, Noele P.; Jahn, Gary C.; Niu, Tianchan; Hartley, David M.

2011-01-01

Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance. PMID:24149031

Use of media and public-domain Internet sources for detection and assessment of plant health threats.

PubMed

Thomas, Carla S; Nelson, Noele P; Jahn, Gary C; Niu, Tianchan; Hartley, David M

2011-09-05

Event-based biosurveillance is a recognized approach to early warning and situational awareness of emerging health threats. In this study, we build upon previous human and animal health work to develop a new approach to plant pest and pathogen surveillance. We show that monitoring public domain electronic media for indications and warning of epidemics and associated social disruption can provide information about the emergence and progression of plant pest infestation or disease outbreak. The approach is illustrated using a case study, which describes a plant pest and pathogen epidemic in China and Vietnam from February 2006 to December 2007, and the role of ducks in contributing to zoonotic virus spread in birds and humans. This approach could be used as a complementary method to traditional plant pest and pathogen surveillance to aid global and national plant protection officials and political leaders in early detection and timely response to significant biological threats to plant health, economic vitality, and social stability. This study documents the inter-relatedness of health in human, animal, and plant populations and emphasizes the importance of plant health surveillance.

The role of integrating natural and social science concepts for risk governance and the design of people-centred early warning systems. Case study from the German-Indonesian Tsunami Early Warning System Project (GITEWS)

NASA Astrophysics Data System (ADS)

Gebert, Niklas; Post, Joachim

2010-05-01

The development of early warning systems are one of the key domains of adaptation to global environmental change and contribute very much to the development of societal reaction and adaptive capacities to deal with extreme events. Especially, Indonesia is highly exposed to tsunami. In average every three years small and medium size tsunamis occur in the region causing damage and death. In the aftermath of the Indian Ocean Tsunami 2004, the German and Indonesian government agreed on a joint cooperation to develop a People Centered End-to-End Early Warning System (GITEWS). The analysis of risk and vulnerability, as an important step in risk (and early warning) governance, is a precondition for the design of effective early warning structures by delivering the knowledge base for developing institutionalized quick response mechanisms of organizations involved in the issuing of a tsunami warning, and of populations exposed to react to warnings and to manage evacuation before the first tsunami wave hits. Thus, a special challenge for developing countries is the governance of complex cross-sectoral and cross-scale institutional, social and spatial processes and requirements for the conceptualization, implementation and optimization of a people centered tsunami early warning system. In support of this, the risk and vulnerability assessment of the case study aims at identifying those factors that constitute the causal structure of the (dis)functionality between the technological warning and the social response system causing loss of life during an emergency situation: Which social groups are likely to be less able to receive and respond to an early warning alert? And, are people able to evacuate in due time? Here, only an interdisciplinary research approach is capable to analyze the socio-spatial and environmental conditions of vulnerability and risk and to produce valuable results for decision makers and civil society to manage tsunami risk in the early warning context. This requires the integration of natural / spatial and social science concepts, methods and data: E.g. a scenario based approach for tsunami inundation modeling was developed to provide decision makers with options to decide up to what level they aim to protect their people and territory, on the contrary household surveys were conducted for the spatial analysis of the evacuation preparedness of the population as a function of place specific hazard, risk, warning and evacuation perception; remote sensing was applied for the spatial analysis (land-use) of the socio-physical conditions of a city and region for evacuation; and existing social / population statistics were combined with land-use data for the precise spatial mapping of the population exposed to tsunami risks. Only by utilizing such a comprehensive assessment approach valuable information for risk governance can be generated. The results are mapped using GIS and designed according to the specific needs of different end-users, such as public authorities involved in the design of warning dissemination strategies, land-use planners (shelter planning, road network configuration) and NGOs mandated to provide education for the general public on tsunami risk and evacuation behavior. The case study of the city of Padang (one of the pilot areas of GITEWS), Indonesia clearly show, that only by intersecting social (vulnerability) and natural hazards research a comprehensive picture on tsunami risk can be provided with which risk governance in the early warning context can be conducted in a comprehensive, systemic and sustainable manner.

FluBreaks: early epidemic detection from Google flu trends.

PubMed

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size. Regions with larger populations (regions 4 and 6) had higher values of EA than region 10 (which had the smallest population) for negative binomial- and Poisson-based algorithms. The difference was 12.5% and 13.5% on average in negative binomial- and Poisson-based algorithms, respectively. We present the first detailed comparative analysis of popular early epidemic detection algorithms on Google Flu Trends data. We note that realizing this opportunity requires moving beyond the cumulative sum and historical limits method-based normal distribution approaches, traditionally employed by the CDC, to negative binomial- and Poisson-based algorithms to deal with potentially noisy search query data from regions with varying population and Internet penetrations. Based on our work, we have developed FluBreaks, an early warning system for flu epidemics using Google Flu Trends.

Early Warning System of Flood Disaster Based on Ultrasonic Sensors and Wireless Technology

NASA Astrophysics Data System (ADS)

Indrasari, W.; Iswanto, B. H.; Andayani, M.

2018-04-01

A flood disaster provides considerable losses to the people who live around the river. To mitigate losses of material due to flood disaster required an early warning system of flood disaster. For that reason, it necessary to design a system that provide alert to the people prior the flood disaster. And this paper describes development of a device for early detection system of flood disasters. This device consists of two ultrasonic sensors as a water level detector, and a water flow sensor as a water flow velocity sensor. The wireless technology and GSM is used as an information medium. The system is designed based on water level conditions in the Katulampa Dam, Bogor. Characterization of water level detector showed that the device effectively works in a range of water level of 14-250 cm, with a maximum relative error of 4.3%. Meanwhile the wireless works properly as far as 75 m, and the SMS transmission time is 8.20 second.

MyShake - A smartphone app to detect earthquake

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.; Schreier, L.; Kwon, Y. W.

2015-12-01

We designed an android app that harnesses the accelerometers in personal smartphones to record earthquake-shaking data for research, hazard information and warnings. The app has the function to distinguish earthquake shakings from daily human activities based on the different patterns behind the movements. It also can be triggered by the traditional earthquake early warning (EEW) system to record for a certain amount of time to collect earthquake data. When the app is triggered by the earthquake-like movements, it sends the trigger information back to our server which contains time and location of the trigger, at the same time, it stores the waveform data on local phone first, and upload to our server later. Trigger information from multiple phones will be processed in real time on the server to find the coherent signal to confirm the earthquakes. Therefore, the app provides the basis to form a smartphone seismic network that can detect earthquake and even provide warnings. A planned public roll-out of MyShake could collect millions of seismic recordings for large earthquakes in many regions around the world.

Detectable Warnings : Detectability by Individuals with Visual Impairments, and Safety and Negotiability on Slopes for Persons with Physical Impairment

DOT National Transportation Integrated Search

1994-09-01

This report presents the results of research on human performance on detectable warning surfaces. The first portion of the report presents an evaluation of the underfoot detectability of nine detectable warning surfaces for persons having varied phys...

Development of a recombinase polymerase amplification assay for the detection of pathogenic Leptospira.

PubMed

Ahmed, Ahmed; van der Linden, Hans; Hartskeerl, Rudy A

2014-05-08

Detection of leptospires based on DNA amplification techniques is essential for the early diagnosis of leptospirosis when anti-Leptospira antibodies are below the detection limit of most serological tests. In middle and low income countries where leptospirosis is endemic, routine implementation of real-time PCR is financially and technically challenging due to the requirement of expensive thermocycler equipment. In this study we report the development and evaluation of a novel isothermal recombinase polymerase amplification assay (RPA) for detection of pathogenic Leptospira based on TwistAmp chemistry. RPA enabled the detection of less than two genome copies per reaction. Retrospective evaluation revealed a high diagnostic accuracy (sensitivity and specificity of 94.7% and 97.7%, respectively) compared to culturing as the reference standard. RPA presents a powerful tool for the early diagnosis of leptospirosis in humans and in animals. Furthermore, it enables the detection of the causative agent in reservoirs and environment, and as such is a valuable adjunct to current tools for surveillance and early outbreak warning.

Development of a Recombinase Polymerase Amplification Assay for the Detection of Pathogenic Leptospira

PubMed Central

Ahmed, Ahmed; van der Linden, Hans; Hartskeerl, Rudy A.

2014-01-01

Detection of leptospires based on DNA amplification techniques is essential for the early diagnosis of leptospirosis when anti-Leptospira antibodies are below the detection limit of most serological tests. In middle and low income countries where leptospirosis is endemic, routine implementation of real-time PCR is financially and technically challenging due to the requirement of expensive thermocycler equipment. In this study we report the development and evaluation of a novel isothermal recombinase polymerase amplification assay (RPA) for detection of pathogenic Leptospira based on TwistAmp chemistry. RPA enabled the detection of less than two genome copies per reaction. Retrospective evaluation revealed a high diagnostic accuracy (sensitivity and specificity of 94.7% and 97.7%, respectively) compared to culturing as the reference standard. RPA presents a powerful tool for the early diagnosis of leptospirosis in humans and in animals. Furthermore, it enables the detection of the causative agent in reservoirs and environment, and as such is a valuable adjunct to current tools for surveillance and early outbreak warning. PMID:24814943

Research on early-warning index of the spatial temperature field in concrete dams.

PubMed

Yang, Guang; Gu, Chongshi; Bao, Tengfei; Cui, Zhenming; Kan, Kan

2016-01-01

Warning indicators of the dam body's temperature are required for the real-time monitoring of the service conditions of concrete dams to ensure safety and normal operations. Warnings theories are traditionally targeted at a single point which have limitations, and the scientific warning theories on global behavior of the temperature field are non-existent. In this paper, first, in 3D space, the behavior of temperature field has regional dissimilarity. Through the Ward spatial clustering method, the temperature field was divided into regions. Second, the degree of order and degree of disorder of the temperature monitoring points were defined by the probability method. Third, the weight values of monitoring points of each regions were explored via projection pursuit. Forth, a temperature entropy expression that can describe degree of order of the spatial temperature field in concrete dams was established. Fifth, the early-warning index of temperature entropy was set up according to the calculated sequential value of temperature entropy. Finally, project cases verified the feasibility of the proposed theories. The early-warning index of temperature entropy is conducive to the improvement of early-warning ability and safety management levels during the operation of high concrete dams.

Building Better Drought Resilience Through Improved Monitoring and Early Warning: Learning From Stakeholders in Europe, the USA, and Australia

NASA Astrophysics Data System (ADS)

Stahl, K.; Hannaford, J.; Bachmair, S.; Tijdeman, E.; Collins, K.; Svoboda, M.; Knutson, C. L.; Wall, N.; Smith, K. H.; Bernadt, T.; Crossman, N. D.; Overton, I. C.; Barker, L. J.; Acreman, M. C.

2016-12-01

With climate projections suggesting that droughts will intensify in many regions in future, improved drought risk management may reduce potential threats to freshwater security across the globe. One aspect that has been called for in this respect is an improvement of the linkage of drought monitoring and early warning, which currently focuses largely on indicators from meteorology and hydrology, to drought impacts on environment and society. However, a survey of existing monitoring and early warning systems globally, that we report on in this contribution, demonstrates that although impacts are being monitored, there is limited work, and certainly little consensus, on how to best achieve this linkage. The Belmont Forum project DrIVER (Drought impacts: Vulnerability thresholds in monitoring and early-warning research) carried out a number of stakeholder workshops in North America, Europe and Australia to elaborate on options for such improvements. A first round of workshops explored current drought management practices among a very diverse range of stakeholders, and their expectations from monitoring and early warning systems (particularly regarding impact characterization). The workshops revealed some disconnects between the indices used in the public early warning systems and those used by local decision-makers, e.g. to trigger drought measures. Follow-up workshops then explored how the links between information at these different scales can be bridged and applied. Impact information plays a key role in this task. This contribution draws on the lessons learned from the transdisciplinary interactions in DrIVER, to enhance the usability of drought monitoring and early-warning systems and other risk management strategies.

Impact of social preparedness on flood early warning systems

NASA Astrophysics Data System (ADS)

Girons Lopez, M.; Di Baldassarre, G.; Seibert, J.

2017-01-01

Flood early warning systems play a major role in the disaster risk reduction paradigm as cost-effective methods to mitigate flood disaster damage. The connections and feedbacks between the hydrological and social spheres of early warning systems are increasingly being considered as key aspects for successful flood mitigation. The behavior of the public and first responders during flood situations, determined by their preparedness, is heavily influenced by many behavioral traits such as perceived benefits, risk awareness, or even denial. In this study, we use the recency of flood experiences as a proxy for social preparedness to assess its impact on the efficiency of flood early warning systems through a simple stylized model and implemented this model using a simple mathematical description. The main findings, which are based on synthetic data, point to the importance of social preparedness for flood loss mitigation, especially in circumstances where the technical forecasting and warning capabilities are limited. Furthermore, we found that efforts to promote and preserve social preparedness may help to reduce disaster-induced losses by almost one half. The findings provide important insights into the role of social preparedness that may help guide decision-making in the field of flood early warning systems.

The Financial Benefit of Early Flood Warnings in Europe

NASA Astrophysics Data System (ADS)

Pappenberger, Florian; Cloke, Hannah L.; Wetterhall, Fredrik; Parker, Dennis J.; Richardson, David; Thielen, Jutta

2015-04-01

Effective disaster risk management relies on science based solutions to close the gap between prevention and preparedness measures. The outcome of consultations on the UNIDSR post-2015 framework for disaster risk reduction highlight the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management in order to save people's lives and property and reduce the overall impact of severe events. In particular, continental and global scale flood forecasting systems provide vital information to various decision makers with which early warnings of floods can be made. Here the potential monetary benefits of early flood warnings using the example of the European Flood Awareness System (EFAS) are calculated based on pan-European Flood damage data and calculations of potential flood damage reductions. The benefits are of the order of 400 Euro for every 1 Euro invested. Because of the uncertainties which accompany the calculation, a large sensitivity analysis is performed in order to develop an envelope of possible financial benefits. Current EFAS system skill is compared against perfect forecasts to demonstrate the importance of further improving the skill of the forecasts. Improving the response to warnings is also essential in reaping the benefits of flood early warnings.

School disengagement as a predictor of dropout, delinquency, and problem substance use during adolescence and early adulthood.

PubMed

Henry, Kimberly L; Knight, Kelly E; Thornberry, Terence P

2012-02-01

Over the past 5 years, a great deal of attention has been paid to the development of early warning systems for dropout prevention. These warning systems use a set of indicators based on official school records to identify youth at risk for dropout and then appropriately target intervention. The current study builds on this work by assessing the extent to which a school disengagement warning index predicts not only dropout but also other problem behaviors during middle adolescence, late adolescence, and early adulthood. Data from the Rochester Youth Development Study (N = 911, 73% male, 68% African American, and 17% Latino) were used to examine the effects of a school disengagement warning index based on official 8th and 9th grade school records on subsequent dropout, as well as serious delinquency, official offending, and problem substance use during middle adolescence, late adolescence, and early adulthood. Results indicate that the school disengagement warning index is robustly related to dropout as well as serious problem behaviors across the three developmental stages, even after controlling for important potential confounders. High school dropout mediates the effect of the warning index on serious problem behaviors in early adulthood.

School Disengagement as a Predictor of Dropout, Delinquency, and Problem Substance Use during Adolescence and Early Adulthood

PubMed Central

Henry, Kimberly L.; Knight, Kelly E.; Thornberry, Terence P.

2015-01-01

Over the past five years, a great deal of attention has been paid to the development of early warning systems for dropout prevention. These warning systems use a set of indicators based on official school records to identify youth at risk for dropout and then appropriately target intervention. The current study builds on this work by assessing the extent to which a school disengagement warning index predicts not only dropout but also other problem behaviors during middle adolescence, late adolescence, and early adulthood. Data from the Rochester Youth Development Study (n=911, 73% male, 68% African American, and 17% Latino) were used to examine the effects of a school disengagement warning index based on official 8th and 9th grade school records on subsequent dropout, as well as serious delinquency, official offending, and problem substance use during middle adolescence, late adolescence, and early adulthood. Results indicate that the school disengagement warning index is robustly related to dropout as well as serious problem behaviors across the three developmental stages, even after controlling for important potential confounders. High school dropout mediates the effect of the warning index on serious problem behaviors in early adulthood. PMID:21523389

Sensor Acquisition for Water Utilities: Survey, Down Selection Process, and Technology List

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alai, M; Glascoe, L; Love, A

2005-06-29

The early detection of the biological and chemical contamination of water distribution systems is a necessary capability for securing the nation's water supply. Current and emerging early-detection technology capabilities and shortcomings need to be identified and assessed to provide government agencies and water utilities with an improved methodology for assessing the value of installing these technologies. The Department of Homeland Security (DHS) has tasked a multi-laboratory team to evaluate current and future needs to protect the nation's water distribution infrastructure by supporting an objective evaluation of current and new technologies. The LLNL deliverable from this Operational Technology Demonstration (OTD) wasmore » to assist the development of a technology acquisition process for a water distribution early warning system. The technology survey includes a review of previous sensor surveys and current test programs and a compiled database of relevant technologies. In the survey paper we discuss previous efforts by governmental agencies, research organizations, and private companies. We provide a survey of previous sensor studies with regard to the use of Early Warning Systems (EWS) that includes earlier surveys, testing programs, and response studies. The list of sensor technologies was ultimately developed to assist in the recommendation of candidate technologies for laboratory and field testing. A set of recommendations for future sensor selection efforts has been appended to this document, as has a down selection example for a hypothetical water utility.« less

[Tourism ecological security early warning of Zhangjiajie, China based on the improved TOPSIS method and the grey GM (1,1)model].

PubMed

Xu, Mei; Liu, Chun la; Li, Dan; Zhong, Xiao Lin

2017-11-01

Tourism ecological security early warning is of great significance both to the coordination of ecological environment protection and tourism industry rapid development in tourism destination, and the sustainable and healthy development of regional social and economy. Firstly, based on the DPSIR model, the tourism ecological security early warning index system of Zhangjiajie was constructed from 5 aspects, which were driving force, pressure, state, impact and response. Then, by using the improved TOPSIS method, the tourism ecological security situation of Zhangjiajie from 2001 to 2014 was analyzed. Lastly, by using the grey GM (1,1) model, the tourism ecological security evolution trend of 2015-2020 was predicted. The results indicated that, on the whole, the close degree of Zhangjiajie's tourism ecological security showed a slightly upward trend during 2001-2014, the warning degree was the moderate warning. In terms of each subsystem, warning degree of the driving force system and the pressure system of Zhangjiajie's tourism ecological secu-rity were on the rise, which evolved from light warning to heavy warning; warning degree of the state system and the impact system had not changed so much, and had been in the moderate warning; warning degree of the response system was on the decline, which changed from huge warning to no warning during 2001-2014. According to the current development trend, the close degree of Zhangjiajie's tourism ecological security would rise further in 2015-2020, and the warning degree would turn from moderate warning into light warning, but the task of coordinating the relationship between tourism development and ecological construction and environmental protection would be still arduous.

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

NASA Astrophysics Data System (ADS)

Intrieri, Emanuele; Bardi, Federica; Fanti, Riccardo; Gigli, Giovanni; Fidolini, Francesco; Casagli, Nicola; Costanzo, Sandra; Raffo, Antonio; Di Massa, Giuseppe; Capparelli, Giovanna; Versace, Pasquale

2017-10-01

A big challenge in terms or landslide risk mitigation is represented by increasing the resiliency of society exposed to the risk. Among the possible strategies with which to reach this goal, there is the implementation of early warning systems. This paper describes a procedure to improve early warning activities in areas affected by high landslide risk, such as those classified as critical infrastructures for their central role in society. This research is part of the project LEWIS (Landslides Early Warning Integrated System): An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines. LEWIS is composed of a susceptibility assessment methodology providing information for single points and areal monitoring systems, a data transmission network and a data collecting and processing center (DCPC), where readings from all monitoring systems and mathematical models converge and which sets the basis for warning and intervention activities. The aim of this paper is to show how logistic issues linked to advanced monitoring techniques, such as big data transfer and storing, can be dealt with compatibly with an early warning system. Therefore, we focus on the interaction between an areal monitoring tool (a ground-based interferometric radar) and the DCPC. By converting complex data into ASCII strings and through appropriate data cropping and average, and by implementing an algorithm for line-of-sight correction, we managed to reduce the data daily output without compromising the capability for performing.

Assessment of Detectable Warning Devices for Specification Compliance or Equivalent Facilitation

DOT National Transportation Integrated Search

1992-12-01

This report evaluates the Americans with Disabilities Act Accessibility Guidelines (ADAAG) specification for detectable : warnings and the applicability of equivalent facilitation to the development of detectable warning devices. Ambiguities : in the...

[Early warning for various internal faults of GIS based on ultraviolet spectroscopy].

PubMed

Zhao, Yu; Wang, Xian-pei; Hu, Hong-hong; Dai, Dang-dang; Long, Jia-chuan; Tian, Meng; Zhu, Guo-wei; Huang, Yun-guang

2015-02-01

As the basis of accurate diagnosis, fault early-warning of gas insulation switchgear (GIS) focuses on the time-effectiveness and the applicability. It would be significant to research the method of unified early-warning for partial discharge (PD) and overheated faults in GIS. In the present paper, SO2 is proposed as the common and typical by-product. The unified monitoring could be achieved through ultraviolet spectroscopy (UV) detection of SO2. The derivative method and Savitzky-Golay filtering are employed for baseline correction and smoothing. The wavelength range of 290-310 nm is selected for quantitative detection of SO2. Through UV method, the spectral interference of SF6 and other complex by-products, e.g., SOF2 and SOF2, can be avoided and the features of trace SO2 in GIS can be extracted. The detection system is featured by compacted structure, low maintenance and satisfactory suitability in filed surveillance. By conducting SF6 decomposition experiments, including two types of PD faults and the overheated faults between 200-400 degrees C, the feasibility of proposed UV method has been verified. Fourier transform infrared spectroscopy and gas chromatography methods can be used for subsequent fault diagnosis. The different decomposition features in two kinds of faults are confirmed and the diagnosis strategy has been briefly analyzed. The main by-products under PD are SOF2 and SO2F2. The generated SO2 is significantly less than SOF2. More carbonous by-products will be generated when PD involves epoxy. By contrast, when the material of heater is stainless steel, SF6 decomposes at about 300 "C and the main by-products in overheated faults are SO2 and SO2F2. When heated over 350 degrees C, SO2 is generated much faster. SOz content stably increases when the GIS fault lasts. The faults types could be preliminarily identified based on the generation features of SO2.

ElarmS Earthquake Early Warning System 2016 Performance and New Research

NASA Astrophysics Data System (ADS)

Chung, A. I.; Allen, R. M.; Hellweg, M.; Henson, I. H.; Neuhauser, D. S.

2016-12-01

The ElarmS earthquake early warning system has been detecting earthquakes throughout California since 2007. It is one of the algorithms that contributes to the West Coast ShakeAlert, a prototype earthquake early warning system being developed for the US West Coast. ElarmS is also running in the Pacific Northwest, and in Israel, Chile, Turkey, and Peru in test mode. We summarize the performance of the ElarmS system over the past year and review some of the more problematic events that the system has encountered. During the first half of 2016 (2016-01-01 through 2016-07-21), ElarmS successfully alerted on all events with ANSS catalog magnitudes M>3 in the Los Angeles area. The mean alert time for these 9 events was just 4.84 seconds. In the San Francisco Bay Area, ElarmS detected 26 events with ANSS catalog magnitudes M>3. The alert times for these events is 9.12 seconds. The alert times are longer in the Bay Area than in the Los Angeles area due to the sparser network of stations in the Bay Area. 7 Bay Area events were not detected by ElarmS. These events occurred in areas where there is less dense station coverage. In addition, ElarmS sent alerts for 13 of the 16 moderately-sized (ANSS catalog magnitudes M>4) events that occurred throughout the state of California. One of those missed events was a M4.5 that occurred far offshore in the northernmost part of the state. The other two missed events occurred inland in regions with sparse station coverage. Over the past year, we have worked towards the implementation of a new filterbank teleseismic filter algorithm, which we will discuss. Other than teleseismic events, a significant cause of false alerts and severely mislocated events is spurious triggers being associated with triggers from a real earthquake. Here, we address new approaches to filtering out problematic triggers.

How do I know if I’ve improved my continental scale flood early warning system?

NASA Astrophysics Data System (ADS)

Cloke, Hannah L.; Pappenberger, Florian; Smith, Paul J.; Wetterhall, Fredrik

2017-04-01

Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.

Constructing early warning information release system in towns enterprise clean production

NASA Astrophysics Data System (ADS)

Yuwen, Huixin; He, Xueqiu; Qian, Xinming; Yuan, Mengqi

2017-08-01

China’s industry boom has not only brought unprecedented prosperity, but also caused the gradual depletion of various resources and the worsening of the natural environment. Experts admit that China is facing serious environmental problem, but they believe that they can seek a new path to overcome it through joint efforts. Early warning information release and clean production are the important concepts in addressing the imminent crisis. Early warning information release system can monitor and forecast the risk that affects the clean production. The author drawn the experiences and lessons from developed countries, combined with China’s reality, put forward countermeasures and suggestions about constructing early warning information release system in process of Chinese town-scaled enterprises clean production.

Early warning signal for interior crises in excitable systems.

PubMed

Karnatak, Rajat; Kantz, Holger; Bialonski, Stephan

2017-10-01

The ability to reliably predict critical transitions in dynamical systems is a long-standing goal of diverse scientific communities. Previous work focused on early warning signals related to local bifurcations (critical slowing down) and nonbifurcation-type transitions. We extend this toolbox and report on a characteristic scaling behavior (critical attractor growth) which is indicative of an impending global bifurcation, an interior crisis in excitable systems. We demonstrate our early warning signal in a conceptual climate model as well as in a model of coupled neurons known to exhibit extreme events. We observed critical attractor growth prior to interior crises of chaotic as well as strange-nonchaotic attractors. These observations promise to extend the classes of transitions that can be predicted via early warning signals.

Landslide susceptibility and early warning model for shallow landslide in Taiwan

NASA Astrophysics Data System (ADS)

Huang, Chun-Ming; Wei, Lun-Wei; Chi, Chun-Chi; Chang, Kan-Tsun; Lee, Chyi-Tyi

2017-04-01

This study aims to development a regional susceptibility model and warning threshold as well as the establishment of early warning system in order to prevent and reduce the losses caused by rainfall-induced shallow landslides in Taiwan. For the purpose of practical application, Taiwan is divided into nearly 185,000 slope units. The susceptibility and warning threshold of each slope unit were analyzed as basic information for disaster prevention. The geological characteristics, mechanism and the occurrence time of landslides were recorded for more than 900 cases through field investigation and interview of residents in order to discuss the relationship between landslides and rainfall. Logistic regression analysis was performed to evaluate the landslide susceptibility and an I3-R24 rainfall threshold model was proposed for the early warning of landslides. The validations of recent landslide cases show that the model was suitable for the warning of regional shallow landslide and most of the cases can be warned 3 to 6 hours in advanced. We also propose a slope unit area weighted method to establish local rainfall threshold on landslide for vulnerable villages in order to improve the practical application. Validations of the local rainfall threshold also show a good agreement to the occurrence time reported by newspapers. Finally, a web based "Rainfall-induced Landslide Early Warning System" is built and connected to real-time radar rainfall data so that landslide real-time warning can be achieved. Keywords: landslide, susceptibility analysis, rainfall threshold

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

PubMed Central

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia. PMID:28704461

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia.

PubMed

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe; Tarantola, Arnaud; Cappelle, Julien

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable-the time elapsed since the first flooding of the year-was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10-1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25-3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.

Modifications of the National Early Warning Score for patients with chronic respiratory disease.

PubMed

Pedersen, N E; Rasmussen, L S; Petersen, J A; Gerds, T A; Østergaard, D; Lippert, A

2018-02-01

The National Early Warning Score (NEWS) uses physiological variables to detect deterioration in hospitalized patients. However, patients with chronic respiratory disease may have abnormal variables not requiring interventions. We studied how the Capital Region of Denmark NEWS Override System (CROS), the Chronic Respiratory Early Warning Score (CREWS) and the Salford NEWS (S-NEWS) affected NEWS total scores and NEWS performance. In an observational study, we included patients with chronic respiratory disease. The frequency of use of CROS and the NEWS total score changes caused by CROS, CREWS and S-NEWS were described. NEWS, CROS, CREWS and S-NEWS were compared using 48-h mortality and intensive care unit (ICU) admission within 48 h as outcomes. We studied 11,266 patients during 25,978 admissions; the use of CROS lowered NEWS total scores in 40% of included patients. CROS, CREWS and S-NEWS had lower sensitivities than NEWS for 48-h mortality and ICU admission. Specificities and PPV were higher. CROS, CREWS and S-NEWS downgraded, respectively, 51.5%, 44.9% and 32.8% of the NEWS total scores from the 'mandatory doctor presence' and 'immediate doctor presence and specialist consultation' total score intervals to lower intervals. Capital Region of Denmark NEWS Override System was frequently used in patients with chronic respiratory disease. CROS, CREWS and S-NEWS reduced sensitivity for 48-h mortality and ICU admission. Using the methodology prevalent in the NEWS literature, we cannot conclude on the safety of these systems. Future prospective studies should investigate the balance between detection rate and alarm fatigue of different systems, or use controlled designs and patient-centred outcomes. © 2017 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Never Use the Complete Search Space: a Concept to Enhance the Optimization Procedure for Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Reuschen, S.; Nowak, W.

2015-12-01

Drinking-water well catchments include many potential sources of contaminations like gas stations or agriculture. Finding optimal positions of early-warning monitoring wells is challenging because there are various parameters (and their uncertainties) that influence the reliability and optimality of any suggested monitoring location or monitoring network.The overall goal of this project is to develop and establish a concept to assess, design and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: a high detection probability, which can be reached by maximizing the "field of vision" of the monitoring network, a long early-warning time such that there is enough time left to install counter measures after first detection, and the overall operating costs of the monitoring network, which should ideally be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, scenario analyses for real data, respectively, wrapped up within the framework of formal multi-objective optimization using a genetic algorithm.In order to speed up the optimization process and to better explore the Pareto-front, we developed a concept that forces the algorithm to search only in regions of the search space where promising solutions can be expected. We are going to show how to define these regions beforehand, using knowledge of the optimization problem, but also how to define them independently of problem attributes. With that, our method can be used with and/or without detailed knowledge of the objective functions.In summary, our study helps to improve optimization results in less optimization time by meaningful restrictions of the search space. These restrictions can be done independently of the optimization problem, but also in a problem-specific manner.

The Early Warning System(EWS) as First Stage to Generate and Develop Shake Map for Bucharest to Deep Vrancea Earthquakes

NASA Astrophysics Data System (ADS)

Marmureanu, G.; Ionescu, C.; Marmureanu, A.; Grecu, B.; Cioflan, C.

2007-12-01

EWS made by NIEP is the first European system for real-time early detection and warning of the seismic waves in case of strong deep earthquakes. EWS uses the time interval (28-32 seconds) between the moment when earthquake is detected by the borehole and surface local accelerometers network installed in the epicenter area (Vrancea) and the arrival time of the seismic waves in the protected area, to deliver timely integrated information in order to enable actions to be taken before a main destructive shaking takes place. Early warning system is viewed as part of an real-time information system that provide rapid information, about an earthquake impeding hazard, to the public and disaster relief organizations before (early warning) and after a strong earthquake (shake map).This product is fitting in with other new product on way of National Institute for Earth Physics, that is, the shake map which is a representation of ground shaking produced by an event and it will be generated automatically following large Vrancea earthquakes. Bucharest City is located in the central part of the Moesian platform (age: Precambrian and Paleozoic) in the Romanian Plain, at about 140 km far from Vrancea area. Above a Cretaceous and a Miocene deposit (with the bottom at roundly 1,400 m of depth), a Pliocene shallow water deposit (~ 700m thick) was settled. The surface geology consists mainly of Quaternary alluvial deposits. Later loess covered these deposits and the two rivers crossing the city (Dambovita and Colentina) carved the present landscape. During the last century Bucharest suffered heavy damage and casualties due to 1940 (Mw = 7.7) and 1977 (Mw = 7.4) Vrancea earthquakes. For example, 32 high tall buildings collapsed and more then 1500 people died during the 1977 event. The innovation with comparable or related systems worldwide is that NIEP will use the EWS to generate a virtual shake map for Bucharest (140 km away of epicentre) immediately after the magnitude is estimated (in 3-4 seconds after the detection in epicentre) and later make corrections by using real time dataflow from each K2 accelerometers installed in Bucharest area, inclusively nonlinear effects. Thus, developing of a near real-time shake map for Bucharest urban area is of highest interest, providing valuable information to the civil defense, decision makers and general public on the area where the ground motion is most severe. EWS made by NIEP can be considered the first stage to generate and develop the shake map for Bucharest to deep Vrancea earthquakes.

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Talathi, S. S.

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizuremore » detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.« less

Development of a GIS-based integrated framework for coastal seiches monitoring and forecasting: A North Jiangsu shoal case study

NASA Astrophysics Data System (ADS)

Qin, Rufu; Lin, Liangzhao

2017-06-01

Coastal seiches have become an increasingly important issue in coastal science and present many challenges, particularly when attempting to provide warning services. This paper presents the methodologies, techniques and integrated services adopted for the design and implementation of a Seiches Monitoring and Forecasting Integration Framework (SMAF-IF). The SMAF-IF is an integrated system with different types of sensors and numerical models and incorporates the Geographic Information System (GIS) and web techniques, which focuses on coastal seiche events detection and early warning in the North Jiangsu shoal, China. The in situ sensors perform automatic and continuous monitoring of the marine environment status and the numerical models provide the meteorological and physical oceanographic parameter estimates. A model outputs processing software was developed in C# language using ArcGIS Engine functions, which provides the capabilities of automatically generating visualization maps and warning information. Leveraging the ArcGIS Flex API and ASP.NET web services, a web based GIS framework was designed to facilitate quasi real-time data access, interactive visualization and analysis, and provision of early warning services for end users. The integrated framework proposed in this study enables decision-makers and the publics to quickly response to emergency coastal seiche events and allows an easy adaptation to other regional and scientific domains related to real-time monitoring and forecasting.

Towards a certification process for tsunami early warning systems

NASA Astrophysics Data System (ADS)

Löwe, Peter; Wächter, Jochen; Hammitzsch, Martin

2013-04-01

The natural disaster of the Boxing Day Tsunami of 2004 was followed by an information catastrophe. Crucial early warning information could not be delivered to the communities under imminent threat, resulting in over 240,000 casualties in 14 countries. This tragedy sparked the development of a new generation of integrated modular Tsunami Early Warning Systems (TEWS). While significant advances were accomplished in the past years, recent events, like the Chile 2010 and the Tohoku 2011 tsunami demonstrate that the key technical challenge for Tsunami Early Warning research on the supranational scale still lies in the timely issuing of status information and reliable early warning messages in a proven workflow. A second challenge stems from the main objective of the Intergovernmental Oceanographic Commission of UNESCO (IOC) Tsunami Programme, the integration of national TEWS towards ocean-wide networks: Each of the increasing number of integrated Tsunami Early Warning Centres has to cope with the continuing evolution of sensors, hardware and software while having to maintain reliable inter-center information exchange services. To avoid future information catastrophes, the performance of all components, ranging from individual sensors, to Warning Centers within their particular end-to-end Warning System Environments, and up to federated Systems of Tsunami Warning Systems has to be regularly validated against defined criteria. Since 2004, GFZ German Research Centre for Geosciences (GFZ) has built up expertise in the field of TEWS. Within GFZ, the Centre for GeoInformation Technology (CeGIT) has focused its work on the geoinformatics aspects of TEWS in two projects already, being the German Indonesian Tsunami Early Warning System (GITEWS) and the Distant Early Warning System (DEWS). This activity is continued in the TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) funded under the European Union's seventh Framework Programme (FP7). TRIDEC focuses on real-time intelligent information management in Earth management and its long-term application: The technical development is based on mature system architecture models and industry standards. The use of standards already applies to the operation of individual TRIDEC reference installations and their interlinking into an integrated service infrastructure for supranational warning services. This is a first step towards best practices and service lifecycles for Early Warning Centre IT service management, including Service Level Agreements (SLA) and Service Certification. While on a global scale the integration of TEWS progresses towards Systems of Systems (SoS), there is still an absence of accredited and reliable certifications for national TEWS or regional Tsunami Early Warning Systems of Systems (TEWSoS). Concepts for TEWS operations have already been published under the guidance of the IOC, and can now be complemented by the recent research advances concerning SoS architecture. Combined with feedback from the real world, such as the NEAMwave 2012 Tsunami exercise in the Mediterranean, this can serve as a starting point to formulate initial requirements for TEWS and TEWSoS certification: Certification activities will cover the establishment of new TEWS and TEWSoS, and also both maintenance and enhancement of existing TEWS/TEWSoS. While the IOC is expected to take a central role in the development of the certification strategy, it remains to be defined which bodies will actually conduct the certification process. Certification requirements and results are likely to become a valuable information source for various target groups, ranging from national policy decision makers, government agency planners, national and local government preparedness officials, TWC staff members, Disaster Responders, the media and the insurance industry.

The performance review of EEWS(Earthquake Early Warning System) about Gyeongju earthquakes with Ml 5.1 and Ml 5.8 in Korea

NASA Astrophysics Data System (ADS)

Park, Jung-Ho; Chi, Heon-Cheol; Lim, In-Seub; Seong, Yun-Jeong; Park, Jihwan

2017-04-01

EEW(Earthquake Early Warning) service to the public has been officially operated by KMA (Korea Meteorological Administration) from 2015 in Korea. For the KMA's official EEW service, KIGAM has adopted ElarmS from UC Berkeley BSL and modified local magnitude relation, 1-D travel time curves and association procedures with real time waveform from about 201 seismic stations of KMA, KIGAM, KINS and KEPRI. There were two moderate size earthquakes with magnitude Ml 5.1 and Ml 5.8 close to Gyeongju city located at the southeastern part of Korea on Sep. 12. 2016. We have checked the performance of EEWS(Earthquake Early Warning System) named as TrigDB by KIGAM reviewing of these two Gyeongju earthquakes. The nearest station to epicenters of two earthquakes Ml 5.1(35.7697 N, 129.1904 E) and Ml 5.8(35.7632 N, 129.1898 E) was MKL which detected P phases in about 2.1 and 3.6 seconds after the origin times respectively. The first events were issued in 6.3 and 7.0 seconds from each origin time. Because of the unstable results on the early steps due to very few stations and unexpected automated analysis, KMA has the policy to wait for more 20 seconds for confirming the reliability. For these events KMA published EEW alarms in about 26 seconds after origin times with M 5.3 and M 5.9 respectively.

ShakeAlert—An earthquake early warning system for the United States west coast

USGS Publications Warehouse

Burkett, Erin R.; Given, Douglas D.; Jones, Lucile M.

2014-08-29

Earthquake early warning systems use earthquake science and the technology of monitoring systems to alert devices and people when shaking waves generated by an earthquake are expected to arrive at their location. The seconds to minutes of advance warning can allow people and systems to take actions to protect life and property from destructive shaking. The U.S. Geological Survey (USGS), in collaboration with several partners, has been working to develop an early warning system for the United States. ShakeAlert, a system currently under development, is designed to cover the West Coast States of California, Oregon, and Washington.

Detecting Tsunami Source Energy and Scales from GNSS & Laboratory Experiments

NASA Astrophysics Data System (ADS)

Song, Y. T.; Yim, S. C.; Mohtat, A.

2016-12-01

Historically, tsunami warnings based on the earthquake magnitude have not been very accurate. According to the 2006 U.S. Government Accountability Office report, an unacceptable 75% false alarm rate has prevailed in the Pacific Ocean (GAO-06-519). One of the main reasons for those inaccurate warnings is that an earthquake's magnitude is not the scale or power of the resulting tsunami. For the last 10 years, we have been developing both theories and algorithms to detect tsunami source energy and scales, instead of earthquake magnitudes per se, directly from real-time Global Navigation Satellite System (GNSS) stations along coastlines for early warnings [Song 2007; Song et al., 2008; Song et al., 2012; Xu and Song 2013; Titov et al, 2016]. Here we will report recent progress on two fronts: 1) Examples of using GNSS in detecting the tsunami energy scales for the 2004 Sumatra M9.1 earthquake, the 2005 Nias M8.7 earthquake, the 2010 M8.8 Chilean earthquake, the 2011 M9.0 Tohoku-Oki earthquake, and the 2015 M8.3 Illapel earthquake. 2) New results from recent state-of-the-art wave-maker experiments and comparisons with GNSS data will also be presented. Related reference: Titov, V., Y. T. Song, L. Tang, E. N. Bernard, Y. Bar-Sever, and Y. Wei (2016), Consistent estimates of tsunami energy show promise for improved early warning, Pur Appl. Geophs., DOI: 10.1007/s00024-016-1312-1. Xu, Z. and Y. T. Song (2013), Combining the all-source Green's functions and the GPS-derived source for fast tsunami prediction - illustrated by the March 2011 Japan tsunami, J. Atmos. Oceanic Tech., jtechD1200201. Song, Y. T., I. Fukumori, C. K. Shum, and Y. Yi (2012), Merging tsunamis of the 2011 Tohoku-Oki earthquake detected over the open ocean, Geophys. Res. Lett., doi:10.1029/2011GL050767. Song, Y. T., L.-L. Fu, V. Zlotnicki, C. Ji, V. Hjorleifsdottir, C.K. Shum, and Y. Yi, 2008: The role of horizontal impulses of the faulting continental slope in generating the 26 December 2004 Tsunami (2007), Ocean Modelling, doi:10.1016/j.ocemod.2007.10.007. Song, Y. T. (2007) Detecting tsunami genesis and scales directly from coastal GPS stations, Geophys. Res. Lett., 34, L19602, doi:10.1029/2007GL031681.

Using SMAP data to improve drought early warning over the US Great Plains

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, N.; Tang, W.

2015-12-01

A drought prone region such as the Great Plains of the United States (US GP) requires credible and actionable drought early warning. Such information cannot simply be extracted from available climate forecasts because of their large uncertainties at regional scales, and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA North American Multi-Model Ensemble experiment (NMME) are much more reliable for winter and spring than for the summer season for the US GP. To mitigate the weaknesses of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies, as the scientific basis for a statistical drought early warning system. This system uses percentile soil moisture anomalies in spring as a key input to provide a probabilistic summer drought early warning. The latter outperforms the dynamic prediction over the US Southern Plains and has been used by the Texas state water agency to support state drought preparedness. A main source of uncertainty for this drought early warning system is the soil moisture input obtained from the NOAA Climate Forecasting System (CFS). We are testing use of the beta version of NASA Soil Moisture Active Passive (SMAP) soil moisture data, along with the Soil Moisture and Ocean Salinity (SMOS), and the long-term Essential Climate Variable Soil Moisture (ECV-SM) soil moisture data, to reduce this uncertainty. Preliminary results based on ECV-SM suggests satellite based soil moisture data could improve early warning of rainfall anomalies over the western US GP with less dense vegetation. The skill degrades over the eastern US GP where denser vegetation is found. We evaluate our SMAP-based drought early warning for 2015 summer against observations.

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs

PubMed Central

Ciamarra, Massimo Pica; Cheong, Siew Ann

2018-01-01

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test. PMID:29538373

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs.

PubMed

Wen, Haoyu; Ciamarra, Massimo Pica; Cheong, Siew Ann

2018-01-01

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test.

A possible space-based tsunami early warning system using observations of the tsunami ionospheric hole.

PubMed

Kamogawa, Masashi; Orihara, Yoshiaki; Tsurudome, Chiaki; Tomida, Yuto; Kanaya, Tatsuya; Ikeda, Daiki; Gusman, Aditya Riadi; Kakinami, Yoshihiro; Liu, Jann-Yenq; Toyoda, Atsushi

2016-12-01

Ionospheric plasma disturbances after a large tsunami can be detected by measurement of the total electron content (TEC) between a Global Positioning System (GPS) satellite and its ground-based receivers. TEC depression lasting for a few minutes to tens of minutes termed as tsunami ionospheric hole (TIH) is formed above the tsunami source area. Here we describe the quantitative relationship between initial tsunami height and the TEC depression rate caused by a TIH from seven tsunamigenic earthquakes in Japan and Chile. We found that the percentage of TEC depression and initial tsunami height are correlated and the largest TEC depressions appear 10 to 20 minutes after the main shocks. Our findings imply that Ionospheric TEC measurement using the existing ground receiver networks could be used in an early warning system for near-field tsunamis that take more than 20 minutes to arrive in coastal areas.

A possible space-based tsunami early warning system using observations of the tsunami ionospheric hole

PubMed Central

Kamogawa, Masashi; Orihara, Yoshiaki; Tsurudome, Chiaki; Tomida, Yuto; Kanaya, Tatsuya; Ikeda, Daiki; Gusman, Aditya Riadi; Kakinami, Yoshihiro; Liu, Jann-Yenq; Toyoda, Atsushi

2016-01-01

Ionospheric plasma disturbances after a large tsunami can be detected by measurement of the total electron content (TEC) between a Global Positioning System (GPS) satellite and its ground-based receivers. TEC depression lasting for a few minutes to tens of minutes termed as tsunami ionospheric hole (TIH) is formed above the tsunami source area. Here we describe the quantitative relationship between initial tsunami height and the TEC depression rate caused by a TIH from seven tsunamigenic earthquakes in Japan and Chile. We found that the percentage of TEC depression and initial tsunami height are correlated and the largest TEC depressions appear 10 to 20 minutes after the main shocks. Our findings imply that Ionospheric TEC measurement using the existing ground receiver networks could be used in an early warning system for near-field tsunamis that take more than 20 minutes to arrive in coastal areas. PMID:27905487

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

[Evaluation and analysis of monitoring and early warning functions of the occupational disease reporting system in China].

PubMed

Zhu, Xiaojun; Li, Tao; Liu, Mengxuan

2015-06-01

To evaluate the monitoring and early warning functions of the occupational disease reporting system right now in China, and to analyze their influencing factors. An improved audit tool (ODIT) was used to score the monitoring and early warning functions with a total score of 10. The nine indices were completeness of information on the reporting form, coverage of the reporting system, accessibility of criteria or guidelines for diagnosis, education and training for physicians, completeness of the reporting system, statistical methods, investigation of special cases, release of monitoring information, and release of early warning information. According to the evaluation, the occupational disease reporting system in China had a score of 5.5 in monitoring existing occupational diseases with a low score for release of monitoring information; the reporting system had a score of 6.5 in early warning of newly occurring occupational diseases with low scores for education and training for physicians as well as completeness of the reporting system. The occupational disease reporting system in China still does not have full function in monitoring and early warning. It is the education and participation of physicians from general hospitals in the diagnosis and treatment of occupational diseases and suspected occupational diseases that need to be enhanced. In addition, the problem of monitoring the incidence of occupational diseases needs to be solved as soon as possible.

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

43. View of CSMR room equipment locator and system checkout ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

43. View of CSMR room equipment locator and system checkout console for detection radars and rearward communication data links in transmitter building no. 102. - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

SEABEE Combat Handbook. Revision

DTIC Science & Technology

1989-02-01

early stages of any biological disease, the general symptoms are fever , malaise, and * Warning, reporting, detection, and inflammation, identification...be thoroughly scrubbed . Contaminated clothing i ilgclwraeee cus fyusolu scontract a disease from biological warfare in spite must be washed in hot...protective masks, skin decontamination caused by thermal radiation and injuries caused kits, and atropine. 19-16 Chapter 19-CHEMICAL, BIOLOGICAL , AND

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak.

PubMed

Song, X X; Zhao, Q; Tao, T; Zhou, C M; Diwan, V K; Xu, B

2018-05-30

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

A SDMS Model: Early Warning Coordination Centres

NASA Astrophysics Data System (ADS)

Santos-Reyes, Jaime

2010-05-01

Following the tsunami disaster in 2004, the General Secretary of the United Nations (UN) Kofi Annan called for a global early warning system for all hazards and for all communities. He also requested the ISDR (International Strategy fort Disaster Reduction) and its UN partners to conduct a global survey of capacities, gaps and opportunities in relation to early warning systems. The produced report, "Global survey of Early Warning Systems", concluded that there are many gaps and shortcomings and that much progress has been made on early warning systems and great capabilities are available around the world. However, it may be argued that an early warning system (EWS) may not be enough to prevent fatalities due to a natural hazard; i.e., it should be seen as part of a ‘wider' or total system. Furthermore, an EWS may work very well when assessed individually but it is not clear whether it will contribute to accomplish the purpose of the ‘total disaster management system'; i.e., to prevent fatalities. For instance, a regional EWS may only work if it is well co-ordinated with the local warning and emergency response systems that ensure that the warning is received, communicated and acted upon by the potentially affected communities. It may be argued that without these local measures being in place, a regional EWS will have little impact in saving lives. Researchers argued that unless people are warned in remote areas, the technology is useless; for instance McGuire [5] argues that: "I have no doubt that the technical element of the warning system will work very well,"…"But there has to be an effective and efficient communications cascade from the warning centre to the fisherman on the beach and his family and the bar owners." Similarly, McFadden [6] states that: "There's no point in spending all the money on a fancy monitoring and a fancy analysis system unless we can make sure the infrastructure for the broadcast system is there,"… "That's going to require a lot of work. If it's a tsunami, you've got to get it down to the last Joe on the beach. This is the stuff that is really very hard." Given the above, the paper argues that there is a need for a systemic approach to early warning centres. Systemic means looking upon things as a system; systemic means seeing pattern and inter-relationship within a complex whole; i.e., to see events as products of the working of a system. System may be defined as a whole which is made of parts and relationships. Given this, ‘failure' may be seen as the product of a system and, within that, see death/injury/property loss etc. as results of the working of systems. This paper proposes a preliminary model of ‘early warning coordination centres' (EWCC); it should be highlighted that an EWCC is a subsystem of the Systemic Disaster Management System (SDMS) model.

Famines in Africa: is early warning early enough?

PubMed Central

Kim, Jeeyon Janet; Guha-Sapir, Debarati

2012-01-01

Following the second Sahelian famine in 1984–1985, major investments were made to establish Early Warning Systems. These systems help to ensure that timely warnings and vulnerability information are available to decision makers to anticipate and avert food crises. In the recent crisis in the Horn of Africa, alarming levels of acute malnutrition were documented from March 2010, and by August 2010, an impending food crisis was forecast. Despite these measures, the situation remained unrecognised, and further deteriorated causing malnutrition levels to grow in severity and scope. By the time the United Nations officially declared famine on 20 July 2011, and the humanitarian community sluggishly went into response mode, levels of malnutrition and mortality exceeded catastrophic levels. At this time, an estimated 11 million people were in desperate and immediate need for food. With warnings of food crises in the Sahel, South Sudan, and forecast of the drought returning to the Horn, there is an immediate need to institutionalize change in the health response during humanitarian emergencies. Early warning systems are only effective if they trigger an early response. PMID:22745628

Famines in Africa: is early warning early enough?

PubMed

Kim, Jeeyon Janet; Guha-Sapir, Debarati

2012-01-01

Following the second Sahelian famine in 1984-1985, major investments were made to establish Early Warning Systems. These systems help to ensure that timely warnings and vulnerability information are available to decision makers to anticipate and avert food crises. In the recent crisis in the Horn of Africa, alarming levels of acute malnutrition were documented from March 2010, and by August 2010, an impending food crisis was forecast. Despite these measures, the situation remained unrecognised, and further deteriorated causing malnutrition levels to grow in severity and scope. By the time the United Nations officially declared famine on 20 July 2011, and the humanitarian community sluggishly went into response mode, levels of malnutrition and mortality exceeded catastrophic levels. At this time, an estimated 11 million people were in desperate and immediate need for food. With warnings of food crises in the Sahel, South Sudan, and forecast of the drought returning to the Horn, there is an immediate need to institutionalize change in the health response during humanitarian emergencies. Early warning systems are only effective if they trigger an early response.

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Jerry; Smoot, James; Kuper, Philip D.

2014-01-01

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Simulating Earthquake Early Warning Systems in the Classroom as a New Approach to Teaching Earthquakes

NASA Astrophysics Data System (ADS)

D'Alessio, M. A.

2010-12-01

A discussion of P- and S-waves seems an ubiquitous part of studying earthquakes in the classroom. Textbooks from middle school through university level typically define the differences between the waves and illustrate the sense of motion. While many students successfully memorize the differences between wave types (often utilizing the first letter as a memory aide), textbooks rarely give tangible examples of how the two waves would "feel" to a person sitting on the ground. One reason for introducing the wave types is to explain how to calculate earthquake epicenters using seismograms and travel time charts -- very abstract representations of earthquakes. Even when the skill is mastered using paper-and-pencil activities or one of the excellent online interactive versions, locating an epicenter simply does not excite many of our students because it evokes little emotional impact, even in students located in earthquake-prone areas. Despite these limitations, huge numbers of students are mandated to complete the task. At the K-12 level, California requires that all students be able to locate earthquake epicenters in Grade 6; in New York, the skill is a required part of the Regent's Examination. Recent innovations in earthquake early warning systems around the globe give us the opportunity to address the same content standard, but with substantially more emotional impact on students. I outline a lesson about earthquakes focused on earthquake early warning systems. The introductory activities include video clips of actual earthquakes and emphasize the differences between the way P- and S-waves feel when they arrive (P arrives first, but is weaker). I include an introduction to the principle behind earthquake early warning (including a summary of possible uses of a few seconds warning about strong shaking) and show examples from Japan. Students go outdoors to simulate P-waves, S-waves, and occupants of two different cities who are talking to one another on cell phones. The culminating activity is for students to "design" an early warning system that will protect their school from nearby earthquakes. The better they design the system, the safer they will be. Each team of students receives a map of faults in the area and possible sites for real-time seismometer installation. Given a fixed budget, they must select the best sites for detecting a likely earthquake. After selecting their locations, teams face-off two-by-two in a tournament of simulated earthquakes. We created animations of a few simulated earthquakes for our institution and have plans to build a web-based version that will allow others to customize the location to their own location and facilitate the competition between teams. Earthquake early warning is both cutting-edge and has huge societal benefits. Instead of teaching our students how to locate epicenters after an earthquake has occurred, we can teach the same content standards while showing them that earthquake science can really save lives.

An early warning and control system for urban, drinking water quality protection: China's experience.

PubMed

Hou, Dibo; Song, Xiaoxuan; Zhang, Guangxin; Zhang, Hongjian; Loaiciga, Hugo

2013-07-01

An event-driven, urban, drinking water quality early warning and control system (DEWS) is proposed to cope with China's urgent need for protecting its urban drinking water. The DEWS has a web service structure and provides users with water quality monitoring functions, water quality early warning functions, and water quality accident decision-making functions. The DEWS functionality is guided by the principles of control theory and risk assessment as applied to the feedback control of urban water supply systems. The DEWS has been deployed in several large Chinese cities and found to perform well insofar as water quality early warning and emergency decision-making is concerned. This paper describes a DEWS for urban water quality protection that has been developed in China.

Preparing for floods: flood forecasting and early warning

NASA Astrophysics Data System (ADS)

Cloke, Hannah

2016-04-01

Flood forecasting and early warning has continued to stride ahead in strengthening the preparedness phases of disaster risk management, saving lives and property and reducing the overall impact of severe flood events. For example, continental and global scale flood forecasting systems such as the European Flood Awareness System and the Global Flood Awareness System provide early information about upcoming floods in real time to various decisionmakers. Studies have found that there are monetary benefits to implementing these early flood warning systems, and with the science also in place to provide evidence of benefit and hydrometeorological institutional outlooks warming to the use of probabilistic forecasts, the uptake over the last decade has been rapid and sustained. However, there are many further challenges that lie ahead to improve the science supporting flood early warning and to ensure that appropriate decisions are made to maximise flood preparedness.

The GNSS-based component for the new Indonesian tsunami early warning centre provided by GITEWS

NASA Astrophysics Data System (ADS)

Falck, C.; Ramatschi, M.; Bartsch, M.; Merx, A.; Hoeberechts, J.; Rothacher, M.

2009-04-01

Introduction Nowadays GNSS technologies are used for a large variety of precise positioning applications. The accuracy can reach the mm level depending on the data analysis methods. GNSS technologies thus offer a high potential to support tsunami early warning systems, e.g., by detection of ground motions due to earthquakes and of tsunami waves on the ocean by GNSS instruments on a buoy. Although GNSS-based precise positioning is a standard method, it is not yet common to apply this technique under tight time constraints and, hence, in the absence of precise satellite orbits and clocks. The new developed GNSS-based component utilises on- and offshore measured GNSS data and is the first system of its kind that was integrated into an operational early warning system. (Indonesian Tsunami Early Warning Centre INATEWS, inaugurated at BMKG, Jakarta on November, 11th 2008) Motivation After the Tsunami event of 26th December 2004 the German government initiated the GITEWS project (German Indonesian Tsunami Early Warning System) to develop a tsunami early warning system for Indonesia. The GFZ Potsdam (German Research Centre for Geosciences) as the consortial leader of GITEWS also covers several work packages, most of them related to sensor systems. The geodetic branch (Department 1) of the GFZ was assigned to develop a GNSS-based component. Brief system description The system covers all aspects from sensor stations with new developed hard- and software designs, manufacturing and installation of stations, real-time data transfer issues, a new developed automatic near real-time data processing and a graphical user interface for early warning centre operators including training on the system. GNSS sensors are installed on buoys, at tide gauges and as real-time reference stations (RTR stations), either stand-alone or co-located with seismic sensors. The GNSS data are transmitted to the warning centre where they are processed in a near real-time data processing chain. For sensors on land the processing system delivers deviations from their normal, mean coordinates. The deviations or so called displacements are indicators for land mass movements which can occur, e.g., due to strong earthquakes. The ground motion information is a valuable source for a fast understanding of an earthquake's mechanism with possible relevance for a potentially following tsunami. By this means the GNSS system supports the decision finding process whether most probably a tsunami has been generated or not. For buoy based GNSS data the processing (differential, with GNSS reference station on land) delivers coordinates as well. Only the vertical component is of interest as it corresponds to the instant sea level height. Deviations to the mean sea level height are an indicator for a possibly passing tsunami wave. The graphical user interface (GUI) of the GNSS system supports both, a quick view for all staff members at the warning centre (24h/7d shifts) and deeper analysis by GNSS experts. The GNSS GUI system is implemented as a web-based application and allows all views to be displayed on different screens at the same time, even at remote locations. This is part of the concept, as it can support the dialogue between warning centre staff on duty or on standby and sensor station maintenance staff. Acknowledgements The GITEWS project (German Indonesian Tsunami Early Warning System) is carried out by a large group of scientists and engineers from (GFZ) German Research Centre for Geosciences and its partners from the German Aerospace Centre (DLR), the Alfred Wegener Institute for Polar and Marine Research (AWI), the GKSS Research Centre, the Konsortium Deutsche Meeresforschung (KDM), the Leibniz Institute for Marine Sciences (IFM-GEOMAR), the United Nations University (UNU), the Federal Institute for Geosciences and Natural Resources (BGR), the German Agency for Technical Cooperation (GTZ) and other international partners. Most relevant partners in Indonesia with respect to the GNSS component of GITEWS are the National Coordinating Agency for Surveys and Mapping (BAKOSURTANAL), the National Metereology and Geophysics Agency (BMKG) and the National Agency for the Assessment and Application of Technology (BPPT). Funding is provided by the German Federal Ministry for Education and Research (BMBF), Grant 03TSU01.

Design of flood early warning system with wifi network based on smartphone

NASA Astrophysics Data System (ADS)

Supani, Ahyar; Andriani, Yuli; Taqwa, Ahmad

2017-11-01

Today, the development using internet of things enables activities surrounding us to be monitored, controlled, predicted and calculated remotely through connections to the internet network such as monitoring activities of long-distance flood warning with information technology. Applying an information technology in the field of flood early warning has been developed in the world, either connected to internet network or not. The internet network that has been done in this paper is the design of WiFi network to access data of rainfall, water level and flood status at any time with a smartphone coming from flood early warning system. The results obtained when test of data accessing with smartphone are in form of rainfall and water level graphs against time and flood status indicators consisting of 3 flood states: Standby 2, Standby 1 and Flood. It is concluded that data are from flood early warning system has been able to accessed and displayed on smartphone via WiFi network in any time and real time.

A real-time biomonitoring system to detect arsenic toxicity by valve movement in freshwater clam Corbicula fluminea.

PubMed

Chen, Wei-Yu; Jou, Li-John; Chen, Suz-Hsin; Liao, Chung-Min

2012-05-01

Arsenic (As) is the element of greatest ecotoxicological concern in aquatic environments. Effective monitoring and diagnosis of As pollution via a biological early warning system is a great challenge for As-affected regions. The purpose of this study was to synthesize water chemistry-based bioavailability and valve daily rhythm in Corbicula fluminea to design a biomonitoring system for detecting waterborne As. We integrated valve daily rhythm dynamic patterns and water chemistry-based Hill dose-response model to build into a programmatic mechanism of inductance-based valvometry technique for providing a rapid and cost-effective dynamic detection system. A LabVIEW graphic control program in a personal computer was employed to demonstrate completely the functional presentation of the present dynamic system. We verified the simulated dissolved As concentrations based on the valve daily rhythm behavior with published experimental data. Generally, the performance of this proposed biomonitoring system demonstrates fairly good applicability to detect waterborne As concentrations when the field As concentrations are less than 1 mg L(-1). We also revealed that the detection times were dependent on As exposure concentrations. This biomonitoring system could particularly provide real-time transmitted information on the waterborne As activity under various aquatic environments. This parsimonious C. fluminea valve rhythm behavior-based real-time biomonitoring system presents a valuable effort to promote the automated biomonitoring and offers early warnings on potential ecotoxicological risks in regions with elevated As exposure concentrations.

ECDC Round Table Report and ProMed-mail most useful international information sources for the Netherlands Early Warning Committee.

PubMed

Bijkerk, Paul; Monnier, Annelie A; Fanoy, Ewout B; Kardamanidis, Katina; Friesema, Ingrid Hm; Knol, Mirjam J

2017-04-06

The Netherlands Early Warning Committee (NEWC) aims to identify infectious diseases causing a potential threat to Dutch public health. Threats are assessed and published as (information) alerts for public health experts. To identify threats from abroad, the NEWC screens 10 sources reporting disease outbreaks each week. To identify the sources essential for complete and timely reporting, we retrospectively analysed 178 international alerts published between 31 January 2013 and 30 January 2014. In addition, we asked the four NEWC coordinators about the required time to scan the information sources. We documented the date and source in which the signal was detected. The ECDC Round Table (RT) Report and ProMED-mail were the most complete and timely sources, reporting 140 of 178 (79%) and 121 of 178 (68%) threats respectively. The combination of both sources reported 169 (95%) of all threats in a timely manner. Adding any of the other sources resulted in minor increases in the total threats found, but considerable additional time investment per additional threat. Only three potential relevant threats (2%) would have been missed by only using the ECDC RT Report and ProMed-mail. We concluded that using only the ECDC RT Report and ProMed-mail to identify threats from abroad maintains a sensitive Early Warning System. This article is copyright of The Authors, 2017.

ECDC Round Table Report and ProMed-mail most useful international information sources for the Netherlands Early Warning Committee

PubMed Central

Monnier, Annelie A; Fanoy, Ewout B; Kardamanidis, Katina; Friesema, Ingrid HM; Knol, Mirjam J

2017-01-01

The Netherlands Early Warning Committee (NEWC) aims to identify infectious diseases causing a potential threat to Dutch public health. Threats are assessed and published as (information) alerts for public health experts. To identify threats from abroad, the NEWC screens 10 sources reporting disease outbreaks each week. To identify the sources essential for complete and timely reporting, we retrospectively analysed 178 international alerts published between 31 January 2013 and 30 January 2014. In addition, we asked the four NEWC coordinators about the required time to scan the information sources. We documented the date and source in which the signal was detected. The ECDC Round Table (RT) Report and ProMED-mail were the most complete and timely sources, reporting 140 of 178 (79%) and 121 of 178 (68%) threats respectively. The combination of both sources reported 169 (95%) of all threats in a timely manner. Adding any of the other sources resulted in minor increases in the total threats found, but considerable additional time investment per additional threat. Only three potential relevant threats (2%) would have been missed by only using the ECDC RT Report and ProMed-mail. We concluded that using only the ECDC RT Report and ProMed-mail to identify threats from abroad maintains a sensitive Early Warning System. PMID:28422006

Developing an automatic classification system of vegetation anomalies for early warning with the ASAP (Anomaly hot Spots of Agricultural Production) system

NASA Astrophysics Data System (ADS)

Meroni, M.; Rembold, F.; Urbano, F.; Lemoine, G.

2016-12-01

Anomaly maps and time profiles of remote sensing derived indicators relevant to monitor crop and vegetation stress can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for SDG 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide monthly warning of production deficits in water-limited agriculture worldwide. The first step is fully automated and aims at classifying each administrative unit (1st sub-national level) into a number of possible warning levels, ranging from "none" to "watch" and up to "extended alarm". The second step involves the verification of the automatic warnings and integration into a short national level analysis by agricultural analysts. In this paper we describe the methodological development of the automatic vegetation anomaly classification system. Warnings are triggered only during the crop growing season, defined by a remote sensing based phenology. The classification takes into consideration the fraction of the agricultural and rangelands area for each administrative unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index (SPI), computed at 1 and 3-month scale) and one biophysical indicator (the cumulative NDVI from the start of the growing season). The severity of the warning thus depends on the timing, the nature and the number of indicators for which an anomaly is detected. The prototype system is using global NDVI images of the METOP sensor, while a second version is being developed based on 1km Modis NDVI with temporal smoothing and near real time filtering. Also a specific water balance model is under development to include agriculture water stress information in addition to the SPI. The monthly warning classification and crop condition assessment will be made available on a website and will strengthen the JRC support to information products based on consensus assessment such as the GEOGLAM Crop Monitor for Early Warning.

New technology for early detection of health threats

NASA Astrophysics Data System (ADS)

Southern, Šárka O.; Lilienthal, Gerald W.

2008-04-01

Governmental agencies charged with protecting the health of the population and agriculture have several main strategic objectives including the detection of harmful agents, the identification of vulnerable biological targets, the prediction of health outcomes and the development of countermeasures. New technologies are urgently needed in several critical areas of bio-chemical defense: economical and minimally invasive biosensors for field use in humans and other species important for agriculture and infrastructure, universal analytical platforms for broad-based, early warnings of threats and technologies guiding the development of countermeasures. A new technology called Stress Response Profiling (SRP) was recently developed by the Gaia Medical Institute. SRP provides a universal analytical platform for monitoring health status based on measurements of physiological stress. The platform is implemented through handheld devices that can be used for noninvasive detection of early-stage health problems. This paper summarizes SRP features, advantages and potential benefits for critical areas of homeland defense.

Tsunami prevention and mitigation necessities and options derived from tsunami risk assessment in Indonesia

NASA Astrophysics Data System (ADS)

Post, J.; Zosseder, K.; Wegscheider, S.; Steinmetz, T.; Mück, M.; Strunz, G.; Riedlinger, T.; Anwar, H. Z.; Birkmann, J.; Gebert, N.

2009-04-01

Risk and vulnerability assessment is an important component of an effective End-to-End Tsunami Early Warning System and therefore contributes significantly to disaster risk reduction. Risk assessment is a key strategy to implement and design adequate disaster prevention and mitigation measures. The knowledge about expected tsunami hazard impacts, exposed elements, their susceptibility, coping and adaptation mechanisms is a precondition for the development of people-centred warning structures, local specific response and recovery policy planning. The developed risk assessment and its components reflect the disaster management cycle (disaster time line) and cover the early warning as well as the emergency response phase. Consequently the components hazard assessment, exposure (e.g. how many people/ critical facilities are affected?), susceptibility (e.g. are the people able to receive a tsunami warning?), coping capacity (are the people able to evacuate in time?) and recovery (are the people able to restore their livelihoods?) are addressed and quantified. Thereby the risk assessment encompasses three steps: (i) identifying the nature, location, intensity and probability of potential tsunami threats (hazard assessment); (ii) determining the existence and degree of exposure and susceptibility to those threats; and (iii) identifying the coping capacities and resources available to address or manage these threats. The paper presents results of the research work, which is conducted in the framework of the GITEWS project and the Joint Indonesian-German Working Group on Risk Modelling and Vulnerability Assessment. The assessment methodology applied follows a people-centred approach to deliver relevant risk and vulnerability information for the purposes of early warning and disaster management. The analyses are considering the entire coastal areas of Sumatra, Java and Bali facing the Sunda trench. Selected results and products like risk maps, guidelines, decision support information and other GIS products will be presented. The focus of the products is on the one hand to provide relevant risk assessment products as decision support to issue a tsunami warning within the early warning stage. On the other hand the maps and GIS products shall provide relevant information to enable local decision makers to act adequately concerning their local risks. It is shown that effective prevention and mitigation measures can be designed based on risk assessment results and information especially when used pro-active and beforehand a disaster strikes. The conducted hazard assessment provides the probability of an area to be affected by a tsunami threat divided into two ranked impact zones. The two divided impact zones directly relate to tsunami warning levels issued by the Early Warning Center and consequently enable the local decision maker to base their planning (e.g. evacuation) accordingly. Within the tsunami hazard assessment several hundred pre-computed tsunami scenarios are analysed. This is combined with statistical analysis of historical event data. Probabilities of tsunami occurrence considering probabilities of different earthquake magnitudes, occurrences of specific wave heights at coast and spatial inundation probability are computed. Hazard assessment is then combined with a comprehensive vulnerability assessment. Here deficits in e.g. people's ability to receive and understand a tsunami warning and deficits in their ability to respond adequately (evacuate on time) are quantified and are visualized for the respective coastal areas. Hereby socio-economic properties (determining peoples ability to understand a warning and to react) are combined with environmental conditions (land cover, slope, population density) to calculate the time needed to evacuate (reach a tsunami safe area derived through the hazard assessment). This is implemented using a newly developed GIS cost-distance weighting approach. For example, the amount of people affected in a certain area is dependent on expected tsunami intensity, inundated area, estimated tsunami arrival time and available time for evacuation. Referring to the Aceh 2004 Tsunami, an estimated amount of people affected (dead/injured) of 21000 for Kabubaten Aceh Jaya and 85000 for Kab. Banda Aceh is in a comparable range with reported values of 19661 and 78417 (JICA 2005) respectively. Hence the established methodology provides reliable estimates of people affected and people's ability to reach a safe area. Based on the spatial explicit detection of e.g. high tsunami risk areas (and the assessed root causes therefore), specific disaster risk reduction and early warning strategies can be designed. For example additional installation of technical warning dissemination device, community based preparedness and awareness programmes (education), structural and non-structural measures (e.g. land use conversion, coastal engineering), effective evacuation, contingency and household recovery aid planning can be employed and/or optimized within high tsunami risk areas as a first priority. In the context of early warning, spatially distributed information like degree of expected hazard impact, exposure of critical facilities (e.g. hospitals, schools), potential people dead/injured depending on available response times, location of safe and shelter areas can be disseminated and used for decision making. Keywords: Tsunami risk, hazard and vulnerability assessment, early warning, tsunami mitigation and prevention, Indonesia

Early Warnings for Local Labor Markets

ERIC Educational Resources Information Center

Matland, Marc A.

1976-01-01

This articles summarizes the National Planning Association's (NPA) experience in its initial efforts to develop an early warning system to anticipate job openings generated in local communities by large Federal procurement contracts. (WL)

Continuous estimates on the earthquake early warning magnitude by use of the near-field acceleration records

NASA Astrophysics Data System (ADS)

Li, Jun; Jin, Xing; Wei, Yongxiang; Zhang, Hongcai

2013-10-01

In this article, the seismic records of Japan's Kik-net are selected to measure the acceleration, displacement, and effective peak acceleration of each seismic record within a certain time after P wave, then a continuous estimation is given on earthquake early warning magnitude through statistical analysis method, and Wenchuan earthquake record is utilized to check the method. The results show that the reliability of earthquake early warning magnitude continuously increases with the increase of the seismic information, the biggest residual happens if the acceleration is adopted to fit earthquake magnitude, which may be caused by rich high-frequency components and large dispersion of peak value in acceleration record, the influence caused by the high-frequency components can be effectively reduced if the effective peak acceleration and peak displacement is adopted, it is estimated that the dispersion of earthquake magnitude obviously reduces, but it is easy for peak displacement to be affected by long-period drifting. In various components, the residual enlargement phenomenon at vertical direction is almost unobvious, thus it is recommended in this article that the effective peak acceleration at vertical direction is preferred to estimate earthquake early warning magnitude. Through adopting Wenchuan strong earthquake record to check the method mentioned in this article, it is found that this method can be used to quickly, stably, and accurately estimate the early warning magnitude of this earthquake, which shows that this method is completely applicable for earthquake early warning.

Detectable Warning Surfaces at Curb Ramps.

ERIC Educational Resources Information Center

Hauger, J. S.; And Others

1996-01-01

Four tests evaluated the need for and effectiveness of detectable warning surfaces at curb ramps for pedestrians with blindness. Results found that the effectiveness of the detectable warning surfaces depended on other aspects of the design of the intersections and on factors such as the density of traffic and the traveler's skills. (CR)

Toward Global Drought Early Warning Capability - Expanding International Cooperation for the Development of a Framework for Monitoring and Forecasting

NASA Technical Reports Server (NTRS)

Pozzi, Will; Sheffield, Justin; Stefanski, Robert; Cripe, Douglas; Pulwarty, Roger; Vogt, Jurgen V.; Heim, Richard R., Jr.; Brewer, Michael J.; Svoboda, Mark; Westerhoff, Rogier;

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure.

PubMed

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-03-27

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate.

No Moving Parts

NASA Technical Reports Server (NTRS)

1998-01-01

Under a NASA SBIR (Small Business Innovative Research), Research International developed the solid state micromachined pump used for cooling electronics in space, circulation of heat transfer fluids on spacecraft, and monitoring fire and gas hazards aboard naval warships. Incorporating Lewis Research Center's pumping technology, commercial applications for this product include both detection of toxins and pollutants in coal mines, and early warning smoke detectors for industrial applications.

Cluster Analysis-Based Approaches for Geospatiotemporal Data Mining of Massive Data Sets for Identification of Forest Threats

Treesearch

Richard Trans Mills; Forrest M Hoffman; Jitendra Kumar; William W. Hargrove

2011-01-01

We investigate methods for geospatiotemporal data mining of multi-year land surface phenology data (250 m2 Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectrometer (MODIS) in this study) for the conterminous United States (CONUS) as part of an early warning system for detecting threats to forest ecosystems. The...

The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health.

PubMed

Mykhalovskiy, Eric; Weir, Lorna

2006-01-01

The recent SARS epidemic has renewed widespread concerns about the global transmission of infectious diseases. In this commentary, we explore novel approaches to global infectious disease surveillance through a focus on an important Canadian contribution to the area--the Global Public Health Intelligence Network (GPHIN). GPHIN is a cutting-edge initiative that draws on the capacity of the Internet and newly available 24/7 global news coverage of health events to create a unique form of early warning outbreak detection. This commentary outlines the operation and development of GPHIN and compares it to ProMED-mail, another Internet-based approach to global health surveillance. We argue that GPHIN has created an important shift in the relationship of public health and news information. By exiting the pyramid of official reporting, GPHIN has created a new monitoring technique that has disrupted national boundaries of outbreak notification, while creating new possibilities for global outbreak response. By incorporating news within the emerging apparatus of global infectious disease surveillance, GPHIN has effectively responded to the global media's challenge to official country reporting of outbreak and enhanced the effectiveness and credibility of international public health.

Ultrasonic Detection of Delamination and Material Characterization of Thermal Barrier Coatings

NASA Astrophysics Data System (ADS)

Chen, Hung-Liang Roger; Zhang, Binwei; Alvin, Mary Anne; Lin, Yun

2012-12-01

This article describes ultrasonic nondestructive evaluation (NDE) to detect the changes of material properties and provide early warning of delamination in thermal barrier coating (TBC) systems. NDE tests were performed on single-crystal René N5 superalloy coupons that were coated with a commercially available MCrAlY bond coat and an air plasma sprayed 7% yttria-stabilized zirconia (YSZ) top coat deposited by Air Plasma Spray method, as well as Haynes 230 superalloy coupons coated with MCrA1Y bond coat, and an electron beam physical vapor deposit of 7% YSZ top coat. The TBC coupons were subjected to either cyclic or isothermal exposure for various lengths of time at temperatures ranging from 900 to 1100 °C. The ultrasonic measurements performed on the coupons had provided an early warning of delamination along the top coat/TGO interface before exposure time, when delamination occurred. The material's property (Young's modulus) of the top coat was estimated using the measured wave speeds. Finite element analysis (FEA) of the ultrasonic wave propagation was conducted on a simplified TBC system to verify experimental observations. The technique developed was also demonstrated on an as-manufactured turbine blade to estimate normalized top coat thickness measurements.

The Tropical Ecology, Assessment and Monitoring (TEAM) Network: An early warning system for tropical rain forests.

PubMed

Rovero, Francesco; Ahumada, Jorge

2017-01-01

While there are well established early warning systems for a number of natural phenomena (e.g. earthquakes, catastrophic fires, tsunamis), we do not have an early warning system for biodiversity. Yet, we are losing species at an unprecedented rate, and this especially occurs in tropical rainforests, the biologically richest but most eroded biome on earth. Unfortunately, there is a chronic gap in standardized and pan-tropical data in tropical forests, affecting our capacity to monitor changes and anticipate future scenarios. The Tropical Ecology, Assessment and Monitoring (TEAM) Network was established to contribute addressing this issue, as it generates real time data to monitor long-term trends in tropical biodiversity and guide conservation practice. We present the Network and focus primarily on the Terrestrial Vertebrates protocol, that uses systematic camera trapping to detect forest mammals and birds, and secondarily on the Zone of Interaction protocol, that measures changes in the anthroposphere around the core monitoring area. With over 3 million images so far recorded, and managed using advanced information technology, TEAM has created the most important data set on tropical forest mammals globally. We provide examples of site-specific and global analyses that, combined with data on anthropogenic disturbance collected in the larger ecosystem where monitoring sites are, allowed us to understand the drivers of changes of target species and communities in space and time. We discuss the potential of this system as a candidate model towards setting up an early warning system that can effectively anticipate changes in coupled human-natural system, trigger management actions, and hence decrease the gap between research and management responses. In turn, TEAM produces robust biodiversity indicators that meet the requirements set by global policies such as the Aichi Biodiversity Targets. Standardization in data collection and public sharing of data in near real time are essential features of such system. Copyright © 2016 Elsevier B.V. All rights reserved.

Future Earth: Reducing Loss By Automating Response to Earthquake Shaking

NASA Astrophysics Data System (ADS)

Allen, R. M.

2014-12-01

Earthquakes pose a significant threat to society in the U.S. and around the world. The risk is easily forgotten given the infrequent recurrence of major damaging events, yet the likelihood of a major earthquake in California in the next 30 years is greater than 99%. As our societal infrastructure becomes ever more interconnected, the potential impacts of these future events are difficult to predict. Yet, the same inter-connected infrastructure also allows us to rapidly detect earthquakes as they begin, and provide seconds, tens or seconds, or a few minutes warning. A demonstration earthquake early warning system is now operating in California and is being expanded to the west coast (www.ShakeAlert.org). In recent earthquakes in the Los Angeles region, alerts were generated that could have provided warning to the vast majority of Los Angelinos who experienced the shaking. Efforts are underway to build a public system. Smartphone technology will be used not only to issue that alerts, but could also be used to collect data, and improve the warnings. The MyShake project at UC Berkeley is currently testing an app that attempts to turn millions of smartphones into earthquake-detectors. As our development of the technology continues, we can anticipate ever-more automated response to earthquake alerts. Already, the BART system in the San Francisco Bay Area automatically stops trains based on the alerts. In the future, elevators will stop, machinery will pause, hazardous materials will be isolated, and self-driving cars will pull-over to the side of the road. In this presentation we will review the current status of the earthquake early warning system in the US. We will illustrate how smartphones can contribute to the system. Finally, we will review applications of the information to reduce future losses.

Progress in Development of an Airborne Turbulence Detection System

NASA Technical Reports Server (NTRS)

Hamilton, David W.; Proctor, Fred H.

2006-01-01

Aircraft encounters with turbulence are the leading cause of in-flight injuries (Tyrvanas 2003) and have occasionally resulted in passenger and crew fatalities. Most of these injuries are caused by sudden and unexpected encounters with severe turbulence in and around convective activity (Kaplan et al 2005). To alleviate this problem, the Turbulence Prediction and Warning Systems (TPAWS) element of NASA s Aviation Safety program has investigated technologies to detect and warn of hazardous in-flight turbulence. This effort has required the numerical modeling of atmospheric convection: 1) for characterizing convectively induced turbulence (CIT) environments, 2) for defining turbulence hazard metrics, and 3) as a means of providing realistic three-dimensional data sets that can be used to test and evaluate turbulence detection sensors. The data sets are being made available to industry and the FAA for certification of future airborne turbulence-detection systems (ATDS) with warning capability. Early in the TPAWS project, a radar-based ATDS was installed and flight tested on NASA s research aircraft, a B-757. This ATDS utilized new algorithms and hazard metrics that were developed for use with existing airborne predictive windshear radars, thus avoiding the installation of new hardware. This system was designed to detect and warn of hazardous CIT even in regions with weak radar reflectivity (i.e. 5-15 dBz). Results from an initial flight test of the ATDS were discussed in Hamilton and Proctor (2002a; 2002b). In companion papers (Proctor et al 2002a; 2002b), a numerical simulation of the most significant encounter from that flight test was presented. Since the presentation of these papers a second flight test has been conducted providing additional cases for examination. In this paper, we will present results from NASA s flight test and a numerical model simulation of a turbulence environment encountered on 30 April 2002. Progress leading towards FAA certification of industry built ATDS will also be discussed.

Multi-model data fusion to improve an early warning system for hypo-/hyperglycemic events.

PubMed

Botwey, Ransford Henry; Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G

2014-01-01

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

The use of early warning scores to recognise and respond to patient deterioration in district nursing.

PubMed

Tucker, Guy; Lusher, Adele

2018-02-02

This discussion article focuses on the literature surrounding early warning scoring systems and their use in primary care, specifically within district nursing. Patient deterioration is a global concern, associated with high mortality rates and avoidable deaths. Early recognition and response by nursing and other health care staff has been attributed to early warning scoring systems (EWSS) and tools. However, the use of equivalent tools in the community appears to be lacking. This review concludes that there is no consensus over the use of EWSS in district nursing and culture of practice is varied, rather than standardised.

European Neolithic societies showed early warning signals of population collapse.

PubMed

Downey, Sean S; Haas, W Randall; Shennan, Stephen J

2016-08-30

Ecosystems on the verge of major reorganization-regime shift-may exhibit declining resilience, which can be detected using a collection of generic statistical tests known as early warning signals (EWSs). This study explores whether EWSs anticipated human population collapse during the European Neolithic. It analyzes recent reconstructions of European Neolithic (8-4 kya) population trends that reveal regime shifts from a period of rapid growth following the introduction of agriculture to a period of instability and collapse. We find statistical support for EWSs in advance of population collapse. Seven of nine regional datasets exhibit increasing autocorrelation and variance leading up to collapse, suggesting that these societies began to recover from perturbation more slowly as resilience declined. We derive EWS statistics from a prehistoric population proxy based on summed archaeological radiocarbon date probability densities. We use simulation to validate our methods and show that sampling biases, atmospheric effects, radiocarbon calibration error, and taphonomic processes are unlikely to explain the observed EWS patterns. The implications of these results for understanding the dynamics of Neolithic ecosystems are discussed, and we present a general framework for analyzing societal regime shifts using EWS at large spatial and temporal scales. We suggest that our findings are consistent with an adaptive cycling model that highlights both the vulnerability and resilience of early European populations. We close by discussing the implications of the detection of EWS in human systems for archaeology and sustainability science.

Earthquake Early Warning: User Education and Designing Effective Messages

NASA Astrophysics Data System (ADS)

Burkett, E. R.; Sellnow, D. D.; Jones, L.; Sellnow, T. L.

2014-12-01

The U.S. Geological Survey (USGS) and partners are transitioning from test-user trials of a demonstration earthquake early warning system (ShakeAlert) to deciding and preparing how to implement the release of earthquake early warning information, alert messages, and products to the public and other stakeholders. An earthquake early warning system uses seismic station networks to rapidly gather information about an occurring earthquake and send notifications to user devices ahead of the arrival of potentially damaging ground shaking at their locations. Earthquake early warning alerts can thereby allow time for actions to protect lives and property before arrival of damaging shaking, if users are properly educated on how to use and react to such notifications. A collaboration team of risk communications researchers and earth scientists is researching the effectiveness of a chosen subset of potential earthquake early warning interface designs and messages, which could be displayed on a device such as a smartphone. Preliminary results indicate, for instance, that users prefer alerts that include 1) a map to relate their location to the earthquake and 2) instructions for what to do in response to the expected level of shaking. A number of important factors must be considered to design a message that will promote appropriate self-protective behavior. While users prefer to see a map, how much information can be processed in limited time? Are graphical representations of wavefronts helpful or confusing? The most important factor to promote a helpful response is the predicted earthquake intensity, or how strong the expected shaking will be at the user's location. Unlike Japanese users of early warning, few Californians are familiar with the earthquake intensity scale, so we are exploring how differentiating instructions between intensity levels (e.g., "Be aware" for lower shaking levels and "Drop, cover, hold on" at high levels) can be paired with self-directed supplemental information to increase the public's understanding of earthquake shaking and protective behaviors.

Early Warning Look Ahead Metrics: The Percent Milestone Backlog Metric

NASA Technical Reports Server (NTRS)

Shinn, Stephen A.; Anderson, Timothy P.

2017-01-01

All complex development projects experience delays and corresponding backlogs of their project control milestones during their acquisition lifecycles. NASA Goddard Space Flight Center (GSFC) Flight Projects Directorate (FPD) teamed with The Aerospace Corporation (Aerospace) to develop a collection of Early Warning Look Ahead metrics that would provide GSFC leadership with some independent indication of the programmatic health of GSFC flight projects. As part of the collection of Early Warning Look Ahead metrics, the Percent Milestone Backlog metric is particularly revealing, and has utility as a stand-alone execution performance monitoring tool. This paper describes the purpose, development methodology, and utility of the Percent Milestone Backlog metric. The other four Early Warning Look Ahead metrics are also briefly discussed. Finally, an example of the use of the Percent Milestone Backlog metric in providing actionable insight is described, along with examples of its potential use in other commodities.

Research on the Risk Early Warning Method of Material Supplier Performance in Power Industry

NASA Astrophysics Data System (ADS)

Chen, Peng; Zhang, Xi

2018-01-01

The early warning of supplier performance risk is still in the initial stage interiorly, and research on the early warning mechanism to identify, analyze and prevent the performance risk is few. In this paper, a new method aiming at marerial supplier performance risk in power industry is proposed, firstly, establishing a set of risk early warning indexes, Then use the ECM method to classify the indexes to form different risk grades. Then, improving Crock Ford risk quantization model by considering three indicators, including the stability of power system, economic losses and successful bid ratio to form the predictive risk grade, and ultimately using short board effect principle to form the ultimate risk grade to truly reflect the supplier performance risk. Finally, making empirical analysis on supplier performance and putting forward the counter measures and prevention strategies for different risks.

Early warning method of Glacial Lake Outburst Floods based on temperature and rainfall

NASA Astrophysics Data System (ADS)

Liu, Jingjing; Su, Pengcheng; Cheng, Zunlan

2017-04-01

Glacial lake outburst floods (GLOFs) are serious disasters in glacial areas. At present, glaciers are retreating while glacial lake area and the outburst risk increases due to the global warming. Therefore, the research of early warning method of GLOFs is important to prevent and reduce the disasters. This paper provides an early warning method using the temperature and rainfall as indices. The daily growth rate of positive antecedent accumulative temperature and the antecedent thirty days accumulative precipitation are calculated for 21 events of GLOF before 2010, based on data from the 21 meteorological stations nearby. The result shows that all the events are above the curve, TV = -0.0193RDC + 3.0018, which can be taken as the early warning threshold curve. This has been verified by the GLOF events in the Ranzeaco glacial lake on 2013-07-05.

Landslide early warning system prototype with GIS analysis indicates by soil movement and rainfall

NASA Astrophysics Data System (ADS)

Artha, Y.; Julian, E. S.

2018-01-01

The aim of this paper is developing and testing of landslide early warning system. The early warning system uses accelerometersas ground movement and tilt-sensing device and a water flow sensor. A microcentroller is used to process the input signal and activate the alarm. An LCD is used to display the acceleration in x,y and z axis. When the soil moved or shifted and rainfall reached 100 mm/day, the alarm rang and signal were sentto the monitoring center via a telemetry system.Data logging information and GIS spatial data can be monitored remotely as tables and graphics as well as in the form of geographical map with the help of web-GIS interface. The system were tested at Kampung Gerendong, Desa Putat Nutug, Kecamatan Ciseeng, Kabupaten Bogor. This area has 3.15 cumulative score, which mean vulnerable to landslide. The results show that the early warning system worked as planned.

How to Decide? Multi-Objective Early-Warning Monitoring Networks for Water Suppliers

NASA Astrophysics Data System (ADS)

Bode, Felix; Loschko, Matthias; Nowak, Wolfgang

2015-04-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources, which cannot be eliminated, especially in urban regions. As a matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs. In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations, to enhance the early warning time before detected contaminations reach the drinking water well, and to minimize the installation and operating costs of the monitoring network. Using multi-objectives optimization, we avoid the problem of having to weight these objectives to a single objective-function. These objectives are clearly competing, and it is impossible to know their mutual trade-offs beforehand - each catchment differs in many points and it is hardly possible to transfer knowledge between geological formations and risk inventories. To make our optimization results more specific to the type of risk inventory in different catchments we do risk prioritization of all known risk sources. Due to the lack of the required data, quantitative risk ranking is impossible. Instead, we use a qualitative risk ranking to prioritize the known risk sources for monitoring. Additionally, we allow for the existence of unknown risk sources that are totally uncertain in location and in their inherent risk. Therefore, they can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well. We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrades) to also cover moderate, tolerable and unknown risk sources. Monitoring networks, which are valid for the remaining risk also cover all other risk sources, but only with a relatively poor early-warning time. The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. It simulates, which potential contaminant plumes from the risk sources would be detectable where and when by all possible candidate positions for monitoring wells. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. These include uncertainty in ambient flow direction of the groundwater, uncertainty of the conductivity field, and different scenarios for the pumping rates of the production wells. To avoid numerical dispersion during the transport simulations, we use particle-tracking random walk methods when simulating transport.

A lightning-based nowcast-warning approach for short-duration rainfall events: Development and testing over Beijing during the warm seasons of 2006-2007

NASA Astrophysics Data System (ADS)

Wu, Fan; Cui, Xiaopeng; Zhang, Da-Lin

2018-06-01

Nowcasting short-duration (i.e., <6 h) rainfall (SDR) events is examined using total [i.e., cloud-to-ground (CG) and intra-cloud (IC)] lightning observations over the Beijing Metropolitan Region (BMR) during the warm seasons of 2006-2007. A total of 928 moderate and 554 intense SDR events, i.e., with the respective hourly rainfall rates (HRR) of 10-20 and ≥20 mm h-1, are utilized to estimate sharp-increasing rates in rainfall and lightning flash, termed as rainfall and lightning jumps, respectively. By optimizing the parameters in a lightning jump and a rainfall jump algorithm, their different jump intensity grades are verified for the above two categories of SDR events. Then, their corresponding graded nowcast-warning models are developed for the moderate and intense SDR events, respectively, with a low-grade warning for hitting more SDR events and a high-grade warning for reducing false alarms. Any issued warning in the nowcast-warning models is designed to last for 2 h after the occurrence of a lightning jump. It is demonstrated that the low-grade warnings can have the probability of detection (POD) of 67.8% (87.0%) and the high-grade warnings have the false alarms ratio (FAR) of 27.0% (22.2%) for the moderate (intense) SDR events, with an averaged lead time of 36.7 (52.0) min. The nowcast-warning models are further validated using three typical heavy-rain-producing storms that are independent from those used to develop the models. Results show that the nowcast-warning models can provide encouraging early warnings for the associated SDR events from the regional to meso-γ scales, indicating that they have a great potential in being applied to the other regions where high-resolution total lightning observations are available.

HRAS: a webserver for early warning of human health risk brought by aflatoxin.

PubMed

Hu, Ruifeng; Zeng, Xu; Gao, Weiwei; Wang, Qian; Liu, Zhihua

2013-02-01

Most people are aware that outdoor air pollution can damage their health, but many do not know that indoor air pollution can also exhibit significant negative health effects. Fungi parasitizing in air conditioning and ventilation systems can be one of indoor air pollution sources. Aflatoxin produced by Aspergillus flavus (A. flavus) became a central focus of indoor air pollution, especially in farmer markets. Therefore we developed an early warning system, Health Risk Assessment System, to estimate the growth rate of A. flavus, predict the amount of aflatoxin and provide early warning information. Firstly, the growth of A. flavus and the production of aflatoxin under different conditions were widely obtained through a comprehensive literature review. Secondly, three mathematical models were established to predict the A. flavus colony growth rate, lag phase duration and aflatoxin content, as functions of temperature and water activity based on present studies. Finally, all the results were evaluated by the user-supplied data using PHP programming language. We utilized the web page to show the results and display warning information. The JpGraph library was used to create a dynamic line chart, refreshing the warning information dynamically in real-time. The HARS provides accurate information for early warning purposes to let us take timely steps to protect ourselves.

Detectable Warnings : Testing and Performance Evaluation at Transit Systems

DOT National Transportation Integrated Search

1994-11-01

A detectable warning is a standardized surface feature, comprised of closely spaced surface projections (truncated domes), built in or applied to walking surfaces to warn visibly impaired individuals of hazards. U.S. DOT regulations, under the Americ...

The impact of Early Warning Score and Rapid Response Systems on nurses' competence: An integrative literature review and synthesis.

PubMed

Jensen, Jørghild Karlotte; Skår, Randi; Tveit, Bodil

2018-04-01

To describe, interpret and synthesise the current research findings on the impact of the Early Warning Score and Rapid Response Systems on nurses' competence in identifying and managing deteriorating patients in general hospital wards. As patient safety initiatives designed to ensure the early identification and management of deteriorating patients, the Early Warning Score and Rapid Response Systems have broad appeal. However, it is still unclear how these systems impact nurses' competence when these systems are used in general hospital wards. CINAHL, PubMed, Cochrane, EMBASE and Ovid MEDLINE databases were systematically searched for relevant articles. Articles were appraised, a thematic analysis was conducted, and similar and divergent perspectives on emergent themes and subthemes were extracted by a team of researchers. Thirty-six studies met the inclusion criteria. The analysis of findings showed how the Early Warning Score and Rapid Response Systems impacted three competence areas: (i) Nurses' competence in assessing and caring for patients related to the subthemes: (a) sensing clinical deterioration and (b) the development of skills and knowledge. (ii). Nurses' competence in referring patients, related to the subthemes: (a) deciding whether to summon help and (b) the language and communication lines in the referral process. (ii) Nurses' coping and mastery experiences. The impact of the Early Warning Score and Rapid Response Systems on nurses' competence in identifying and managing deteriorating patients is beneficial but also somewhat contradictory. A greater understanding of nurses' development of competence when using the Early Warning Score and Rapid Response Systems will facilitate the design of implementation strategies and the use of these systems to improve practice. © 2017 John Wiley & Sons Ltd.

Can we develop an effective early warning system for volcanic eruptions using `off the shelf' webcams and low-light cameras?

NASA Astrophysics Data System (ADS)

Harrild, M.; Webley, P. W.; Dehn, J.

2016-12-01

An effective early warning system to detect volcanic activity is an invaluable tool, but often very expensive. Detecting and monitoring precursory events, thermal signatures, and ongoing eruptions in near real-time is essential, but conventional methods are often logistically challenging, expensive, and difficult to maintain. Our investigation explores the use of `off the shelf' webcams and low-light cameras, operating in the visible to near-infrared portions of the electromagnetic spectrum, to detect and monitor volcanic incandescent activity. Large databases of webcam imagery already exist at institutions around the world, but are often extremely underutilised and we aim to change this. We focus on the early detection of thermal signatures at volcanoes, using automated scripts to analyse individual images for changes in pixel brightness, allowing us to detect relative changes in thermally incandescent activity. Primarily, our work focuses on freely available streams of webcam images from around the world, which we can download and analyse in near real-time. When changes in activity are detected, an alert is sent to the users informing them of the changes in activity and a need for further investigation. Although relatively rudimentary, this technique provides constant monitoring for volcanoes in remote locations and developing nations, where it is not financially viable to deploy expensive equipment. We also purchased several of our own cameras, which were extensively tested in controlled laboratory settings with a black body source to determine their individual spectral response. Our aim is to deploy these cameras at active volcanoes knowing exactly how they will respond to varying levels of incandescence. They are ideal for field deployments as they are cheap (0-1,000), consume little power, are easily replaced, and can provide telemetered near real-time data. Data from Shiveluch volcano, Russia and our spectral response lab experiments are presented here.

Early Warning Systems: Re-Engaging Chronic Truants

ERIC Educational Resources Information Center

Chorneau, Tom

2012-01-01

School attendance can be an early indicator that something is going wrong with a student. Gathering, analyzing, and acting on attendance information is a first step toward school improvement. Meanwhile, the majority of the states are moving to build and enhance what are called "early warning systems," intended to flag at-risk students during their…

Detection of early warning signals of forest mortality in California

NASA Astrophysics Data System (ADS)

Liu, Y.; Kumar, M.; Katul, G. G.; Porporato, A. M.

2017-12-01

Massive forest mortality was observed in California during the most recent drought. Owing to complex interactions of physiological mechanisms under stress, prediction of climate-induced forest mortality using dynamic global vegetation models remains fraught with uncertainty. Given that forest ecosystems approaching mortality tend to exhibit reduction in resilience, we evaluate the time-varying resilience from time series of satellite images to detect early warning signals (EWSs) of mortality. Four metrics of EWSs are used: (1) low greenness, (2) high empirical autocorrelation of greenness, (3) high autocorrelation inferred using a Bayesian dynamic linear model considering the influence of seasonality and climate conditions, and (4) low recovery rate inferred from the drift term in the Langevin equation describing stochastic dynamics. Spatial accuracy and lead-time of these EWSs are evaluated by comparing the EWSs against observed mortality from aerial surveys conducted by the US Forest Service. Our results show that most forested areas in California that underwent mortality exhibit a EWS with a lead time of three months to two years ahead of observed mortality. Notably, EWS is also detected in some areas without mortality, suggesting reduced resilience during drought. Furthermore, the influence of the previous drought (2007-2009) may have propagated into the recent drought (2012-2016) through reduced resilience, hence contributing to the massive forest mortality observed recently. Methodologies developed in this study for detection of EWS will improve the near-term predictability of forest mortality, thus providing crucial information for forest and water resource management.

Evaluation of appropriate sensor specifications for space based ballistic missile detection

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin; Wendelstein, Norbert

2012-10-01

The detection and tracking of ballistic missiles (BMs) during launch or cloud break using satellite based electro-optical (EO) sensors is a promising possibility for pre-instructing early warning and fire control radars. However, the successful detection of a BM is depending on the applied infrared (IR)-channel, as emission and reflection of threat and background vary in different spectral (IR-) bands and for different observation scenarios. In addition, the spatial resolution of the satellite based system also conditions the signal-to-clutter-ratio (SCR) and therefore the predictability of the flight path. Generally available satellite images provide data in spectral bands, which are suitable for remote sensing applications and earth surface observations. However, in the fields of BM early warning, these bands are not of interest making the simulation of background data essential. The paper focuses on the analysis of IR-bands suitable for missile detection by trading off the suppression of background signature against threat signal strength. This comprises a radiometric overview of the background radiation in different spectral bands for different climates and seasons as well as for various cloud types and covers. A brief investigation of the BM signature and its trajectory within a threat scenario is presented. Moreover, the influence on the SCR caused by different observation scenarios and varying spatial resolution are pointed out. The paper also introduces the software used for simulating natural background spectral radiance images, MATISSE ("Advanced Modeling of the Earth for Environment and Scenes Simulation") by ONERA [1].

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides

NASA Astrophysics Data System (ADS)

Piciullo, Luca; Dahl, Mads-Peter; Devoli, Graziella; Colleuille, Hervé; Calvello, Michele

2017-06-01

The Norwegian national landslide early warning system (LEWS), operational since 2013, is managed by the Norwegian Water Resources and Energy Directorate and was designed for monitoring and forecasting the hydrometeorological conditions potentially triggering slope failures. Decision-making in the LEWS is based upon rainfall thresholds, hydrometeorological and real-time landslide observations as well as on landslide inventory and susceptibility maps. Daily alerts are issued throughout the country considering variable size warning zones. Warnings are issued once per day for the following 3 days and can be updated according to weather forecasts and information gathered by the monitoring network. The performance of the LEWS operational in Norway has been evaluated applying the EDuMaP method, which is based on the computation of a duration matrix relating number of landslides and warning levels issued in a warning zone. In the past, this method has been exclusively employed to analyse the performance of regional early warning models considering fixed warning zones. Herein, an original approach is proposed for the computation of the elements of the duration matrix in the case of early warning models issuing alerts on variable size areas. The approach has been used to evaluate the warnings issued in Western Norway, in the period 2013-2014, considering two datasets of landslides. The results indicate that the landslide datasets do not significantly influence the performance evaluation, although a slightly better performance is registered for the smallest dataset. Different performance results are observed as a function of the values adopted for one of the most important input parameters of EDuMaP, the landslide density criterion (i.e. setting the thresholds to differentiate among classes of landslide events). To investigate this issue, a parametric analysis has been conducted; the results of the analysis show significant differences among computed performances when absolute or relative landslide density criteria are considered.

Avian influenza surveillance of wild birds

USGS Publications Warehouse

Slota, Paul

2007-01-01

The President's National Strategy for Pandemic Influenza directs federal agencies to expand the surveillance of United States domestic livestock and wildlife to ensure early warning of hightly pathogenic avian influenza (HPAI) in the U.S. The immediate concern is a potential introduction of HPAI H5N1 virus into the U.S. The presidential directive resulted in the U.S. Interagency Strategic Plan for Early Detection of H5N1 Highly Pathogenic Avian Influenza in Wild Migratory Birds (referred to as the Wild Bird Surveillance Plan or the Plan).

The value of vital sign trends for detecting clinical deterioration on the wards

PubMed Central

Churpek, Matthew M; Adhikari, Richa; Edelson, Dana P

2016-01-01

Aim Early detection of clinical deterioration on the wards may improve outcomes, and most early warning scores only utilize a patient’s current vital signs. The added value of vital sign trends over time is poorly characterized. We investigated whether adding trends improves accuracy and which methods are optimal for modelling trends. Methods Patients admitted to five hospitals over a five-year period were included in this observational cohort study, with 60% of the data used for model derivation and 40% for validation. Vital signs were utilized to predict the combined outcome of cardiac arrest, intensive care unit transfer, and death. The accuracy of models utilizing both the current value and different trend methods were compared using the area under the receiver operating characteristic curve (AUC). Results A total of 269,999 patient admissions were included, which resulted in 16,452 outcomes. Overall, trends increased accuracy compared to a model containing only current vital signs (AUC 0.78 vs. 0.74; p<0.001). The methods that resulted in the greatest average increase in accuracy were the vital sign slope (AUC improvement 0.013) and minimum value (AUC improvement 0.012), while the change from the previous value resulted in an average worsening of the AUC (change in AUC −0.002). The AUC increased most for systolic blood pressure when trends were added (AUC improvement 0.05). Conclusion Vital sign trends increased the accuracy of models designed to detect critical illness on the wards. Our findings have important implications for clinicians at the bedside and for the development of early warning scores. PMID:26898412

The value of vital sign trends for detecting clinical deterioration on the wards.

PubMed

Churpek, Matthew M; Adhikari, Richa; Edelson, Dana P

2016-05-01

Early detection of clinical deterioration on the wards may improve outcomes, and most early warning scores only utilize a patient's current vital signs. The added value of vital sign trends over time is poorly characterized. We investigated whether adding trends improves accuracy and which methods are optimal for modelling trends. Patients admitted to five hospitals over a five-year period were included in this observational cohort study, with 60% of the data used for model derivation and 40% for validation. Vital signs were utilized to predict the combined outcome of cardiac arrest, intensive care unit transfer, and death. The accuracy of models utilizing both the current value and different trend methods were compared using the area under the receiver operating characteristic curve (AUC). A total of 269,999 patient admissions were included, which resulted in 16,452 outcomes. Overall, trends increased accuracy compared to a model containing only current vital signs (AUC 0.78 vs. 0.74; p<0.001). The methods that resulted in the greatest average increase in accuracy were the vital sign slope (AUC improvement 0.013) and minimum value (AUC improvement 0.012), while the change from the previous value resulted in an average worsening of the AUC (change in AUC -0.002). The AUC increased most for systolic blood pressure when trends were added (AUC improvement 0.05). Vital sign trends increased the accuracy of models designed to detect critical illness on the wards. Our findings have important implications for clinicians at the bedside and for the development of early warning scores. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Exploring the utility of real-time hydrologic data for landslide early warning

NASA Astrophysics Data System (ADS)

Mirus, B. B.; Smith, J. B.; Becker, R.; Baum, R. L.; Koss, E.

2017-12-01

Early warning systems can provide critical information for operations managers, emergency planners, and the public to help reduce fatalities, injuries, and economic losses due to landsliding. For shallow, rainfall-triggered landslides early warning systems typically use empirical rainfall thresholds, whereas the actual triggering mechanism involves the non-linear hydrological processes of infiltration, evapotranspiration, and hillslope drainage that are more difficult to quantify. Because hydrologic monitoring has demonstrated that shallow landslides are often preceded by a rise in soil moisture and pore-water pressures, some researchers have developed early warning criteria that attempt to account for these antecedent wetness conditions through relatively simplistic storage metrics or soil-water balance modeling. Here we explore the potential for directly incorporating antecedent wetness into landslide early warning criteria using recent landslide inventories and in-situ hydrologic monitoring near Seattle, WA, and Portland, OR. We use continuous, near-real-time telemetered soil moisture and pore-water pressure data measured within a few landslide-prone hillslopes in combination with measured and forecasted rainfall totals to inform easy-to-interpret landslide initiation thresholds. Objective evaluation using somewhat limited landslide inventories suggests that our new thresholds based on subsurface hydrologic monitoring and rainfall data compare favorably to the capabilities of existing rainfall-only thresholds for the Seattle area, whereas there are no established rainfall thresholds for the Portland area. This preliminary investigation provides a proof-of-concept for the utility of developing landslide early warning criteria in two different geologic settings using real-time subsurface hydrologic measurements from in-situ instrumentation.

Effects of stressor characteristics on early warning signs of critical transitions and "critical coupling" in complex dynamical systems.

PubMed

Blume, Steffen O P; Sansavini, Giovanni

2017-12-01

Complex dynamical systems face abrupt transitions into unstable and catastrophic regimes. These critical transitions are triggered by gradual modifications in stressors, which push the dynamical system towards unstable regimes. Bifurcation analysis can characterize such critical thresholds, beyond which systems become unstable. Moreover, the stochasticity of the external stressors causes small-scale fluctuations in the system response. In some systems, the decomposition of these signal fluctuations into precursor signals can reveal early warning signs prior to the critical transition. Here, we present a dynamical analysis of a power system subjected to an increasing load level and small-scale stochastic load perturbations. We show that the auto- and cross-correlations of bus voltage magnitudes increase, leading up to a Hopf bifurcation point, and further grow until the system collapses. This evidences a gradual transition into a state of "critical coupling," which is complementary to the established concept of "critical slowing down." Furthermore, we analyze the effects of the type of load perturbation and load characteristics on early warning signs and find that gradient changes in the autocorrelation provide early warning signs of the imminent critical transition under white-noise but not for auto-correlated load perturbations. Furthermore, the cross-correlation between all voltage magnitude pairs generally increases prior to and beyond the Hopf bifurcation point, indicating "critical coupling," but cannot provide early warning indications. Finally, we show that the established early warning indicators are oblivious to limit-induced bifurcations and, in the case of the power system model considered here, only react to an approaching Hopf bifurcation.

The effect of adult Early Warning Systems education on nurses' knowledge, confidence and clinical performance: A systematic review.

PubMed

Saab, Mohamad M; McCarthy, Bridie; Andrews, Tom; Savage, Eileen; Drummond, Frances J; Walshe, Nuala; Forde, Mary; Breen, Dorothy; Henn, Patrick; Drennan, Jonathan; Hegarty, Josephine

2017-11-01

This review aims to determine the effect of adult Early Warning Systems education on nurses' knowledge, confidence and clinical performance. Early Warning Systems support timely identification of clinical deterioration and prevention of avoidable deaths. Several educational programmes have been designed to help nurses recognize and manage deteriorating patients. Little is known as to the effectiveness of these programmes. Systematic review. Academic Search Complete, CINAHL, MEDLINE, PsycINFO, PsycARTICLES, Psychology and Behavioral Science Collection, SocINDEX and the UK & Ireland Reference Centre, EMBASE, the Turning Research Into Practice database, the Cochrane Central Register of Controlled Trials (CENTRAL) and Grey Literature sources were searched between October and November 2015. This is a quantitative systematic review using Cochrane methods. Studies published between January 2011 - November 2015 in English were sought. The risk of bias, level of evidence and the quality of evidence per outcome were assessed. Eleven articles with 10 studies were included. Nine studies addressed clinical performance, four addressed knowledge and two addressed confidence. Knowledge, vital signs recording and Early Warning Score calculation were improved in the short term. Two interventions had no effect on nurses' response to clinical deterioration and use of communication tools. This review highlights the importance of measuring outcomes using standardized tools and valid and reliable instruments. Using longitudinal designs, researchers are encouraged to investigate the effect of Early Warning Systems educational programmes. These can include interactive e-learning, on-site interdisciplinary Early Warning Scoring systems training sessions and simulated scenarios. © 2017 John Wiley & Sons Ltd.

Study on warning radius of diffuse reflection laser warning based on fish-eye lens

NASA Astrophysics Data System (ADS)

Chen, Bolin; Zhang, Weian

2013-09-01

The diffuse reflection type of omni-directional laser warning based on fish-eye lens is becoming more and more important. As one of the key parameters of warning system, the warning radius should be put into investigation emphatically. The paper firstly theoretically analyzes the energy detected by single pixel of FPA detector in the system under complicated environment. Then the least energy detectable by each single pixel of the system is computed in terms of detector sensitivity, system noise, and minimum SNR. Subsequently, by comparison between the energy detected by single pixel and the least detectable energy, the warning radius is deduced from Torrance-Sparrow five-parameter semiempirical statistic model. Finally, a field experiment was developed to validate the computational results. It has been found that the warning radius has a close relationship with BRDF parameters of the irradiated target, propagation distance, angle of incidence, and detector sensitivity, etc. Furthermore, an important fact is shown that the experimental values of warning radius are always less than that of theoretical ones, due to such factors as the optical aberration of fish-eye lens, the transmissivity of narrowband filter, and the packing ratio of detector.

Earth Observations for Early Detection of Agricultural Drought: Contributions of the Famine Early Warning Systems Network (FEWS NET)

NASA Astrophysics Data System (ADS)

Budde, M. E.; Funk, C.; Husak, G. J.; Peterson, P.; Rowland, J.; Senay, G. B.; Verdin, J. P.

2016-12-01

The U.S. Geological Survey (USGS) has a long history of supporting the use of Earth observation data for food security monitoring through its role as an implementing partner of the Famine Early Warning Systems Network (FEWS NET) program. The use of remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and changing climatic regimes has been a core activity in monitoring FEWS NET countries. In recent years, it has become a requirement that FEWS NET apply monitoring and modeling frameworks at global scales to assess emerging crises in regions that FEWS NET does not traditionally monitor. USGS FEWS NET, in collaboration with the University of California, Santa Barbara, has developed a number of new global applications of satellite observations, derived products, and efficient tools for visualization and analyses to address these requirements. (1) A 35-year quasi-global (+/- 50 degrees latitude) time series of gridded rainfall estimates, the Climate Hazards Infrared Precipitation with Stations (CHIRPS) dataset, based on infrared satellite imagery and station observations. Data are available as 5-day (pentadal) accumulations at 0.05 degree spatial resolution. (2) Global actual evapotranspiration data based on application of the Simplified Surface Energy Balance (SSEB) model using 10-day MODIS Land Surface Temperature composites at 1-km resolution. (3) Production of global expedited MODIS (eMODIS) 10-day NDVI composites updated every 5 days. (4) Development of an updated Early Warning eXplorer (EWX) tool for data visualization, analysis, and sharing. (5) Creation of stand-alone tools for enhancement of gridded rainfall data and trend analyses. (6) Establishment of an agro-climatology analysis tool and knowledge base for more than 90 countries of interest to FEWS NET. In addition to these new products and tools, FEWS NET has partnered with the GEOGLAM community to develop a Crop Monitor for Early Warning (CM4EW) which brings together global expertise in agricultural monitoring to reach consensus on growing season status of "countries at risk". Such engagements will result in enhanced capabilities for extending our monitoring efforts globally.

Use of a novel electronic maternal surveillance system to generate automated alerts on the labor and delivery unit.

PubMed

Klumpner, Thomas T; Kountanis, Joanna A; Langen, Elizabeth S; Smith, Roger D; Tremper, Kevin K

2018-06-26

Maternal early warning systems reduce maternal morbidity. We developed an electronic maternal surveillance system capable of visually summarizing the labor and delivery census and identifying changes in clinical status. Automatic page alerts to clinical providers, using an algorithm developed at our institution, were incorporated in an effort to improve early detection of maternal morbidity. We report the frequency of pages generated by the system. To our knowledge, this is the first time such a system has been used in peripartum care. Alert criteria were developed after review of maternal early warning systems, including the Maternal Early Warning Criteria (MEWC). Careful consideration was given to the frequency of pages generated by the surveillance system. MEWC notification criteria were liberalized and a paging algorithm was created that triggered paging alerts to first responders (nurses) and then managing services due to the assumption that paging all clinicians for each vital sign triggering MEWC would generate an inordinate number of pages. For preliminary analysis, to determine the effect of our automated paging algorithm on alerting frequency, the paging frequency of this system was compared to the frequency of vital signs meeting the Maternal Early Warning Criteria (MEWC). This retrospective analysis was limited to a sample of 34 patient rooms uniquely capable of storing every vital sign reported by the bedside monitor. Over a 91-day period, from April 1 to July 1, 2017, surveillance was conducted from 64 monitored beds, and the obstetrics service received one automated page every 2.3 h. The most common triggers for alerts were for hypertension and tachycardia. For the subset of 34 patient rooms uniquely capable of real-time recording, one vital sign met the MEWC every 9.6 to 10.3 min. Anecdotally, the system was well-received. This novel electronic maternal surveillance system is designed to reduce cognitive bias and improve timely clinical recognition of maternal deterioration. The automated paging algorithm developed for this software dramatically reduces paging frequency compared to paging for isolated vital sign abnormalities alone. Long-term, prospective studies will be required to determine its impact on patient outcomes.

Early warning reporting categories analysis of recall and complaints data.

DOT National Transportation Integrated Search

2001-12-31

This analysis was performed to assist the National Highway Traffic Safety Administration (NHTSA) in identifying components and systems to be included in early warning reporting (EWR) categories that would be based upon historical safety-related recal...

Automatic Hypocenter Determination Method in JMA Catalog and its Application

NASA Astrophysics Data System (ADS)

Tamaribuchi, K.

2017-12-01

The number of detectable earthquakes around Japan has increased by developing the high-sensitivity seismic observation network. After the 2011 Tohoku-oki earthquake, the number of detectable earthquakes have dramatically increased due to its aftershocks and induced earthquakes. This enormous number of earthquakes caused inability of manually determination of all the hypocenters. The Japan Meteorological Agency (JMA), which produces the earthquake catalog in Japan, has developed a new automatic hypocenter determination method and started its operation from April 1, 2016. This method (named PF method; Phase combination Forward search method) can determine the hypocenters of earthquakes that occur simultaneously by searching for the optimal combination of P- and S-wave arrival times and the maximum amplitudes using a Bayesian estimation technique. In the 2016 Kumamoto earthquake sequence, we successfully detected about 70,000 aftershocks automatically during the period from April 14 to the end of May, and this method contributed to the real-time monitoring of the seismic activity. Furthermore, this method can be also applied to the Earthquake Early Warning (EEW). Application of this method for EEW is called the IPF method and has been used as the hypocenter determination method of the EEW system in JMA from December 2016. By developing this method further, it is possible to contribute to not only speeding up the catalog production, but also improving reliability of the early warning.

Geospatiotemporal Data Mining of Remotely Sensed Phenology for Unsupervised Forest Threat Detection

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Vulli, S. S.; Hargrove, W. W.; Spruce, J.

2010-12-01

Hargrove and Hoffman have previously developed and applied a scalable geospatiotemporal data mining approach to define a set of categorical, multivariate classes or states for describing and tracking the behavior of ecosystem properties through time within a multi-dimensional phase or state space. The method employs a standard k-means cluster analysis with enhancements that reduce the number of required comparisons, dramatically accelerating iterative convergence. In support of efforts by the USDA Forest Service to develop a National Early Warning System for Forest Disturbances, we have applied this geospatiotemporal cluster analysis procedure to annual phenology patterns derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for unsupervised change detection. We will present initial results from the analysis of seven years of 250-m MODIS NDVI data for the conterminous United States. While determining what constitutes a "normal" phenological pattern for any given location is challenging due to interannual climate variability, a spatially varying climate change trend, and the relatively short record of MODIS NDVI observations, these results demonstrate the utility of the method for detecting significant mortality events, like the progressive damage from mountain pine beetle, and suggest that the technique may be successfully implemented as a key component in an early warning system for identifying forest threats from natural and anthropogenic disturbances at a continental scale.

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems

USGS Publications Warehouse

Gsell, Alena Sonia; Scharfenberger, Ulrike; Ozkundakci, Deniz; Walters, Annika W.; Hansson, Lars-Anders; Janssen, Annette B. G.; Noges, Peeter; Reid, Philip; Schindler, Daniel; van Donk, Ellen; Dakos, Vasilis; Adrian, Rita

2016-01-01

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems.

PubMed

Gsell, Alena Sonia; Scharfenberger, Ulrike; Özkundakci, Deniz; Walters, Annika; Hansson, Lars-Anders; Janssen, Annette B G; Nõges, Peeter; Reid, Philip C; Schindler, Daniel E; Van Donk, Ellen; Dakos, Vasilis; Adrian, Rita

2016-12-13

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

Sensor Fusion of Position- and Micro-Sensors (MEMS) integrated in a Wireless Sensor Network for movement detection in landslide areas

NASA Astrophysics Data System (ADS)

Arnhardt, Christian; Fernández-Steeger, Tomas; Azzam, Rafig

2010-05-01

Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement technologies were chosen. The MEMS-Sensors are acceleration-, tilt- and barometric pressure sensors. The positionsensors are draw wire and linear displacement transducers. In first laboratory tests the accuracy and resolution were investigated. The tests showed good results for all sensors. For example tilt-movements can be monitored with an accuracy of +/- 0,06° and a resolution of 0,1°. With the displacement transducer change in length of >0,1mm is possible. Apart from laboratory tests, field tests in South France and Germany were done to prove data stability and movement detection under real conditions. The results obtained were very satisfying, too. In the next step the combination of numerous sensors (sensor fusion) of the same type (redundancy) or different types (complementary) was researched. Different experiments showed that there is a high concordance between identical sensor-types. According to different sensor parameters (sensitivity, accuracy, resolution) some sensor-types can identify changes earlier. Taking this into consideration, good correlations between different kinds of sensors were achieved, too. Thus the experiments showed that combination of sensors is possible and this could improve the detection of movement and movement rate but also outliers. Based on this results various algorithms were setup that include different statistical methods (outlier tests, testing of hypotheses) and procedures from decision theories (Hurwicz-criteria). These calculation formulas will be implemented in the spatial data infrastructure (SDI) for the further data processing and validation. In comparison with today existing mainly punctually working monitoring systems, the application of wireless sensor networks in combination with low-cost, but precise micro-sensors provides an inexpensive and easy to set up monitoring system also in large areas. The correlation of same but also different sensor-types permits a good data control. Thus the sensor fusion is a promising tool to detect movement more reliable and thus contributes essential to the improvement of Early Warning Systems.

New insights into flood warning reception and emergency response by affected parties

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Müller, Meike; Schröter, Kai; Thieken, Annegret H.

2017-11-01

Flood damage can be mitigated if the parties at risk are reached by flood warnings and if they know how to react appropriately. To gain more knowledge about warning reception and emergency response of private households and companies, surveys were undertaken after the August 2002 and the June 2013 floods in Germany. Despite pronounced regional differences, the results show a clear overall picture: in 2002, early warnings did not work well; e.g. many households (27 %) and companies (45 %) stated that they had not received any flood warnings. Additionally, the preparedness of private households and companies was low in 2002, mainly due to a lack of flood experience. After the 2002 flood, many initiatives were launched and investments undertaken to improve flood risk management, including early warnings and an emergency response in Germany. In 2013, only a small share of the affected households (5 %) and companies (3 %) were not reached by any warnings. Additionally, private households and companies were better prepared. For instance, the share of companies which have an emergency plan in place has increased from 10 % in 2002 to 34 % in 2013. However, there is still room for improvement, which needs to be triggered mainly by effective risk and emergency communication. The challenge is to continuously maintain and advance an integrated early warning and emergency response system even without the occurrence of extreme floods.

Availability and Reliability of Disaster Early Warning Systems and the IT Infrastructure Library

NASA Astrophysics Data System (ADS)

Wächter, J.; Loewe, P.

2012-12-01

The Boxing Day Tsunami of 2004 caused an information catastrophy. Crucial early warning information could not be delivered to the communities under imminent threat, resulting in over 240,000 casualties in 14 countries. This tragedy sparked the development of a new generation of integrated modular Tsunami Early Warning Systems (TEWS). While significant advances were accomplished in the past years, recent events, like the Chile 2010 and the Tohoku 2011 tsunami demonstrate that the key technical challenge for Tsunami Early Warning research on the supranational scale still lies in the timely issuing of status information and reliable early warning messages. A key challenge stems from the main objective of the IOC Tsunami Programme, the integration of national TEWS towards ocean-wide networks: Each of the increasing number of integrated Tsunami Early Warning Centres has to cope with the continuing evolution of sensors, hardware and software while having to maintain reliable inter-center information exchange services. To avoid future information catastrophes, the performance of all components, ranging from sensors to Warning Centers, has to be regularly validated against defined criteria. This task is complicated by the fact that in term of ICT system life cycles tsunami are very rare event resulting in very difficult framing conditions to safeguard the availability and reliability of TWS. Since 2004, GFZ German Research Centre for Geosciences (GFZ) has built up expertise in the field of TEWS. Within GFZ, the Centre for GeoInformation Technology (CEGIT) has focused its work on the geoinformatics aspects of TEWS in two projects already: The German Indonesian Tsunami Early Warning System (GITEWS) funded by the German Federal Ministry of Education and Research (BMBF) and the Distant Early Warning System (DEWS), a European project funded under the sixth Framework Programme (FP6). These developments are continued in the TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) funded under the European Union's seventh Framework Programme (FP7). This ongoing project focuses on real-time intelligent information management in Earth management and its long-term application. All technical development in TRIDEC is based on mature system architecture models and industry standards. The use of standards applies also to the operation of individual TRIDEC reference installations and their interlinking into an integrated service infrastructure for supranational warning services: A set of best practices for IT service management is used to align the TEWS software services with the requirements by the Early Warning Centre management by defining Service Level Agreements (SLA) and ensuring appliance. For this, the concept of service lifecycles is adapted for the TEWS domain, which is laid out in the IT Infrastructure Library (ITIL) by the United Kingdom's Office of Government Commerce (OGC). The cyclic procedures, tasks and checklists described by ITIL are used to establish a baseline to plan, implement, and maintain TEWS service components in the long run. This allows to ensure compliance with given international TEWS standards and to measure improvement of the provided services against a gold-standard.

2010 Kansas City Plant Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-06-20

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Savannah River Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-09-12

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Hanford Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety, and Security

2009-07-16

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Idaho National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-09-26

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-08-16

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Pantex Plant Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-07-31

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Hanford Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-14

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Pantex Plant Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-06-29

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Sandia National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-10-26

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Pantex Plant Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-19

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Argonne National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-06-20

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

Multiple-time scales analysis of physiological time series under neural control

NASA Technical Reports Server (NTRS)

Peng, C. K.; Hausdorff, J. M.; Havlin, S.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.

1998-01-01

We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.

Prototype Earthquake Early Warning System for Areas of Highest Seismic Risk in the Western U.S.

NASA Astrophysics Data System (ADS)

Bock, Y.; Geng, J.; Goldberg, D.; Saunders, J. K.; Haase, J. S.; Squibb, M. B.; Melgar, D.; Crowell, B. W.; Clayton, R. W.; Yu, E.; Walls, C. P.; Mann, D.; Mencin, D.; Mattioli, G. S.

2015-12-01

We report on a prototype earthquake early warning system for the Western U.S. based on GNSS (GPS+GLONASS) observations, and where available collocated GNSS and accelerometer data (seismogeodesy). We estimate with latency of 2-3 seconds GNSS displacement waveforms from more than 120 stations, focusing on the southern segment of the San Andreas fault, the Hayward and Rodgers Creek faults and Cascadia. The displacements are estimated using precise point positioning with ambiguity resolution (PPP-AR), which provides for efficient processing of hundreds of "clients" within the region of interest with respect to a reference frame well outside the expected zone of deformation. The GNSS displacements are useful for alleviating magnitude saturation concerns, rapid earthquake magnitude estimation using peak ground displacements, CMT solutions and finite fault slip models. However, GNSS alone is insufficient for strict earthquake early warning (i.e., P wave detection). Therefore, we employ a self-contained seismogeodetic technique, where collocations of GNSS and accelerometer instruments are available, to estimate real-time displacement and velocity waveforms using PPP-AR with accelerometers (PPP-ARA). Using the velocity waveforms we can detect the P wave arrival for earthquakes of interest (>M 5.5), estimate a hypocenter, S wave propagation, and earthquake magnitude using Pd scaling relationships within seconds. Currently we are gearing up to receive observatory-grade accelerometer data from the CISN. We have deployed 25 inexpensive MEMS accelerometers at existing GNSS stations. The SIO Geodetic Modules that control the flow of the GNSS and accelerometer data are being upgraded with in situ PPP-ARA and P wave picking. In situ processing allows us to use the data at the highest sampling rate of the GNSS receiver (10 Hz or higher), in combination with the 100 Hz accelerometer data. Adding the GLONASS data allows for increased precision in the vertical, an important factor in P wave detection, and by reducing outliers, increasing the number of visible satellites and significantly reducing the time required for reinitialization of phase ambiguities. We plan to make our displacement and velocity waveforms available to the USGS ShakeAlert system and others in Earthworm format.

REWSET: A prototype seismic and tsunami early warning system in Rhodes island, Greece

NASA Astrophysics Data System (ADS)

Papadopoulos, Gerasimos; Argyris, Ilias; Aggelou, Savvas; Karastathis, Vasilis

2014-05-01

Tsunami warning in near-field conditions is a critical issue in the Mediterranean Sea since the most important tsunami sources are situated within tsunami wave travel times starting from about five minutes. The project NEARTOWARN (2012-2013) supported by the EU-DG ECHO contributed substantially to the development of new tools for the near-field tsunami early warning in the Mediterranean. One of the main achievements is the development of a local warning system in the test-site of Rhodes island (Rhodes Early Warning System for Earthquakes and Tsunamis - REWSET). The system is composed by three main subsystems: (1) a network of eight seismic early warning devices installed in four different localities of the island, one in the civil protection, another in the Fire Brigade and another two in municipality buildings; (2) two radar-type (ultrasonic) tide-gauges installed in the eastern coastal zine of the island which was selected since research on the historical earthquake and tsunami activity has indicated that the most important, near-field tsunami sources are situated offshore to the east of Rhodes; (3) a crisis Geographic Management System (GMS), which is a web-based and GIS-based application incorporating a variety of thematic maps and other information types. The seismic early warning devices activate by strong (magnitude around 6 or more) earthquakes occurring at distances up to about 100 km from Rhodes, thus providing immediate mobilization of the civil protection. The tide-gauges transmit sea level data, while during the crisis the GMS supports decisions to be made by civil protection. In the near future it is planned the REWSET system to be integrated with national and international systems. REWSET is a prototype which certainly could be developed in other coastal areas of the Mediterranean and beyond.

Seismic Monitoring of Permafrost During Controlled Thaw: An Active-Source Experiment Using a Surface Orbital Vibrator and Fiber-Optic DAS Arrays

NASA Astrophysics Data System (ADS)

Dou, S.; Wood, T.; Lindsey, N.; Ajo Franklin, J. B.; Freifeld, B. M.; Gelvin, A.; Morales, A.; Saari, S.; Ekblaw, I.; Wagner, A. M.; Daley, T. M.; Robertson, M.; Martin, E. R.; Ulrich, C.; Bjella, K.

2016-12-01

Thawing of permafrost can cause ground deformations that threaten the integrity of civil infrastructure. It is essential to develop early warning systems that can identify critically warmed permafrost and issue warnings for hazard prevention and control. Seismic methods can play a pivotal role in such systems for at least two reasons: First, seismic velocities are indicative of mechanical strength of the subsurface and thus are directly relevant to engineering properties; Second, seismic velocities in permafrost systems are sensitive to pre-thaw warming, which makes it possible to issue early warnings before the occurrence of hazardous subsidence events. However, several questions remain: What are the seismic signatures that can be effectively used for early warning of permafrost thaw? Can seismic methods provide enough warning times for hazard prevention and control? In this study, we investigate the feasibility of using permanently installed seismic networks for early warnings of permafrost thaw. We conducted continuous active-source seismic monitoring of permafrost that was under controlled heating at CRREL's Fairbanks permafrost experiment station. We used a permanently installed surface orbital vibrator (SOV) as source and surface-trenched DAS arrays as receivers. The SOV is characterized by its excellent repeatability, automated operation, high energy level, and the rich frequency content (10-100 Hz) of the generated wavefields. The fiber-optic DAS arrays allow continuous recording of seismic data with dense spatial sampling (1-meter channel spacing), low cost, and low maintenance. This combination of SOV-DAS provides unique seismic datasets for observing time-lapse changes of warming permafrost at the field scale, hence providing an observational basis for design and development of early warning systems for permafrost thaw.

Identifying early-warning signals of critical transitions with strong noise by dynamical network markers

PubMed Central

Liu, Rui; Chen, Pei; Aihara, Kazuyuki; Chen, Luonan

2015-01-01

Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher-dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamical network marker (DNM) to signal the impending critical transition using the transformed higher-dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems. PMID:26647650

Usage of Wireless Sensor Networks in a service based spatial data infrastructure for Landslide Monitoring and Early Warning

NASA Astrophysics Data System (ADS)

Arnhardt, C.; Fernandez-Steeger, T. M.; Walter, K.; Kallash, A.; Niemeyer, F.; Azzam, R.; Bill, R.

2007-12-01

The joint project Sensor based Landslide Early Warning System (SLEWS) aims at a systematic development of a prototyping alarm- and early warning system for the detection of mass movements by application of an ad hoc wireless sensor network (WSN). Next to the development of suitable sensor setups, sensor fusion and network fusion are applied to enhance data quality and reduce false alarm rates. Of special interest is the data retrieval, processing and visualization in GI-Systems. Therefore a suitable serviced based Spatial Data Infrastructure (SDI) will be developed with respect to existing and upcoming Open Geospatial Consortium (OGC) standards.The application of WSN provides a cheap and easy to set up solution for special monitoring and data gathering in large areas. Measurement data from different low-cost transducers for deformation observation (acceleration, displacement, tilting) is collected by distributed sensor nodes (motes), which interact separately and connect each other in a self-organizing manner. Data are collected and aggregated at the beacon (transmission station) and further operations like data pre-processing and compression can be performed. The WSN concept provides next to energy efficiency, miniaturization, real-time monitoring and remote operation, but also new monitoring strategies like sensor and network fusion. Since not only single sensors can be integrated at single motes either cross-validation or redundant sensor setups are possible to enhance data quality. The planned monitoring and information system will include a mobile infrastructure (information technologies and communication components) as well as methods and models to estimate surface deformation parameters (positioning systems). The measurements result in heterogeneous observation sets that have to be integrated in a common adjustment and filtering approach. Reliable real-time information will be obtained using a range of sensor input and algorithms, from which early warnings and prognosis may be derived. Implementation of sensor algorithms is an important task to form the business logic. This will be represented in self-contained web-based processing services (WPS). In the future different types of sensor networks can communicate via an infrastructure of OGC services using an interoperable way by standardized protocols as the Sensor Markup Language (SensorML) and Observations & Measurements Schema (O&M). Synchronous and asynchronous information services as the Sensor Alert Service (SAS) and the Web Notification Services (WNS) will provide defined users and user groups with time-critical readings from the observation site. Techniques using services for visualizing mapping data (WMS), meta data (CSW), vector (WFS) and raster data (WCS) will range from high detailed expert based output to fuzzy graphical warning elements.The expected results will be an advancement regarding classical alarm and early warning systems as the WSN are free scalable, extensible and easy to install.

77 FR 55605 - Early Warning Reporting, Foreign Defect Reporting, and Motor Vehicle and Equipment Recall...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-10

... requires quarterly reporting of early warning information: Production information; information on incidents... manufacturers, and other equipment manufacturers) and the annual production of the entity. The EWR information... vehicle type as part of [[Page 55608

Coral Reef Early Warning System (CREWS) RPC Experiment

NASA Technical Reports Server (NTRS)

Estep, Leland; Spruce, Joseph P.; Hall, Callie

2007-01-01

This viewgraph document reviews the background, objectives, methodology, validation, and present status of the Coral Reef Early Warning System (CREWS) Rapid Prototyping Capability (RPC) experiment. The potential NASA contribution to CREWS Decision Support Tool (DST) centers on remotely sensed imagery products.

Early warning systems for the management of chronic heart failure: a systematic literature review of cost-effectiveness models.

PubMed

Albuquerque De Almeida, Fernando; Al, Maiwenn; Koymans, Ron; Caliskan, Kadir; Kerstens, Ankie; Severens, Johan L

2018-04-01

Describing the general and methodological characteristics of decision-analytical models used in the economic evaluation of early warning systems for the management of chronic heart failure patients and performing a quality assessment of their methodological characteristics is expected to provide concise and useful insight to inform the future development of decision-analytical models in the field of heart failure management. Areas covered: The literature on decision-analytical models for the economic evaluation of early warning systems for the management of chronic heart failure patients was systematically reviewed. Nine electronic databases were searched through the combination of synonyms for heart failure and sensitive filters for cost-effectiveness and early warning systems. Expert commentary: The retrieved models show some variability with regards to their general study characteristics. Overall, they display satisfactory methodological quality, even though some points could be improved, namely on the consideration and discussion of any competing theories regarding model structure and disease progression, identification of key parameters and the use of expert opinion, and uncertainty analyses. A comprehensive definition of early warning systems and further research under this label should be pursued. To improve the transparency of economic evaluation publications, authors should make available detailed technical information regarding the published models.

Research and application of a novel hybrid air quality early-warning system: A case study in China.

PubMed

Li, Chen; Zhu, Zhijie

2018-06-01

As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency. Copyright © 2018 Elsevier B.V. All rights reserved.

Community-based early warning systems for flood risk mitigation in Nepal

NASA Astrophysics Data System (ADS)

Smith, Paul J.; Brown, Sarah; Dugar, Sumit

2017-03-01

This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2-3 to 7-8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure

PubMed Central

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-01-01

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate. PMID:29584699

An Envelope Based Feedback Control System for Earthquake Early Warning: Reality Check Algorithm

NASA Astrophysics Data System (ADS)

Heaton, T. H.; Karakus, G.; Beck, J. L.

2016-12-01

Earthquake early warning systems are, in general, designed to be open loop control systems in such a way that the output, i.e., the warning messages, only depend on the input, i.e., recorded ground motions, up to the moment when the message is issued in real-time. We propose an algorithm, which is called Reality Check Algorithm (RCA), which would assess the accuracy of issued warning messages, and then feed the outcome of the assessment back into the system. Then, the system would modify its messages if necessary. That is, we are proposing to convert earthquake early warning systems into feedback control systems by integrating them with RCA. RCA works by continuously monitoring and comparing the observed ground motions' envelopes to the predicted envelopes of Virtual Seismologist (Cua 2005). Accuracy of magnitude and location (both spatial and temporal) estimations of the system are assessed separately by probabilistic classification models, which are trained by a Sparse Bayesian Learning technique called Automatic Relevance Determination prior.

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities.

PubMed

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the "S&P 500 1987" bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

PubMed Central

Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

2011-01-01

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

Detection of rain events in radiological early warning networks with spectro-dosimetric systems

NASA Astrophysics Data System (ADS)

Dąbrowski, R.; Dombrowski, H.; Kessler, P.; Röttger, A.; Neumaier, S.

2017-10-01

Short-term pronounced increases of the ambient dose equivalent rate, due to rainfall are a well-known phenomenon. Increases in the same order of magnitude or even below may also be caused by a nuclear or radiological event, i.e. by artificial radiation. Hence, it is important to be able to identify natural rain events in dosimetric early warning networks and to distinguish them from radiological events. Novel spectrometric systems based on scintillators may be used to differentiate between the two scenarios, because the measured gamma spectra provide significant nuclide-specific information. This paper describes three simple, automatic methods to check whether an dot H*(10) increase is caused by a rain event or by artificial radiation. These methods were applied to measurements of three spectrometric systems based on CeBr3, LaBr3 and SrI2 scintillation crystals, investigated and tested for their practicability at a free-field reference site of PTB.

Most Common Foodborne Pathogens and Mycotoxins on Fresh Produce: A Review of Recent Outbreaks.

PubMed

Yeni, F; Yavaş, S; Alpas, H; Soyer, Y

2016-07-03

Every year millions of people are affected and thousands of them die due to infections and intoxication as a result of foodborne outbreaks, which also cause billions of dollars' worth of damage, public health problems, and agricultural product loss. A considerable portion of these outbreaks is related to fresh produce and caused by foodborne pathogens on fresh produce and mycotoxins. Escherichia coli O104:H4 outbreak, occurred in Germany in 2011, has attracted a great attention on foodborne outbreaks caused by contaminated fresh produce, and especially the vulnerability and gaps in the early warning and notification networks in the surveillance systems in all around the world. In the frame of this paper, we reviewed the most common foodborne pathogens on fresh produce, traceback investigations of the outbreaks caused by these pathogens, and lastly international early warning and notification systems, including PulseNet International and Rapid Alert System for Food and Feed, aiming to detect foodborne outbreaks.

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Ryan, Robert E.; McKellip, Rodney

2008-01-01

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William

2014-01-01

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

CISN ShakeAlert: Faster Warning Information Through Multiple Threshold Event Detection in the Virtual Seismologist (VS) Early Warning Algorithm

NASA Astrophysics Data System (ADS)

Cua, G. B.; Fischer, M.; Caprio, M.; Heaton, T. H.; Cisn Earthquake Early Warning Project Team

2010-12-01

The Virtual Seismologist (VS) earthquake early warning (EEW) algorithm is one of 3 EEW approaches being incorporated into the California Integrated Seismic Network (CISN) ShakeAlert system, a prototype EEW system that could potentially be implemented in California. The VS algorithm, implemented by the Swiss Seismological Service at ETH Zurich, is a Bayesian approach to EEW, wherein the most probable source estimate at any given time is a combination of contributions from a likehihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS codes have been running in real-time at the Southern California Seismic Network since July 2008, and at the Northern California Seismic Network since February 2009. We discuss recent enhancements to the VS EEW algorithm that are being integrated into CISN ShakeAlert. We developed and continue to test a multiple-threshold event detection scheme, which uses different association / location approaches depending on the peak amplitudes associated with an incoming P pick. With this scheme, an event with sufficiently high initial amplitudes can be declared on the basis of a single station, maximizing warning times for damaging events for which EEW is most relevant. Smaller, non-damaging events, which will have lower initial amplitudes, will require more picks to initiate an event declaration, with the goal of reducing false alarms. This transforms the VS codes from a regional EEW approach reliant on traditional location estimation (and the requirement of at least 4 picks as implemented by the Binder Earthworm phase associator) into an on-site/regional approach capable of providing a continuously evolving stream of EEW information starting from the first P-detection. Real-time and offline analysis on Swiss and California waveform datasets indicate that the multiple-threshold approach is faster and more reliable for larger events than the earlier version of the VS codes. In addition, we provide evolutionary estimates of the probability of false alarms (PFA), which is an envisioned output stream of the CISN ShakeAlert system. The real-time decision-making approach envisioned for CISN ShakeAlert users, where users specify a threshhold PFA in addition to thresholds on peak ground motion estimates, has the potential to increase the available warning time for users with high tolerance to false alarms without compromising the needs of users with lower tolerances to false alarms.

Onsite Portable Alarm System - Its Merit and Application

NASA Astrophysics Data System (ADS)

Saita, J.; Sato, T.; Nakamura, Y.

2007-12-01

Recently an existence of the earthquake early warning system (EEWS) becomes popular. In general, the EEWS will be installed in a fixed observation site and it may consist of several separated components such as a sensing portion, A/D converter, an information processing potion and so on. The processed information for warning may be transmitted to network via fixed communication line, and therefore this kind of alarm system is called as Network Alarm System. On the other hand, after the severe earthquake damage, it is very important to save the disaster victims immediately. These rescue staffs are also under the risk of aftershocks and need a local alarm not depending on the network, so this kind of alarm can be called as Onsite Alarm. But the common early warning system is too complex to set onsite temporary, and even if possible to install, the alarm is too late to receive at the epicentral area. However, the new generation earthquake early warning system FREQL can issue the P wave alarm by minimum 0.2 seconds after P wave detection. And FREQL is characterized as the unique all-in-one seismometer with power unit. At the time of the 2004 Niigata-Ken-Chuetsu earthquake, a land slide attacked a car just passing. A hyper rescue team of Tokyo Fire Department pulled the survivor, one baby, from the land slide area. During their activity the rescue team was exposed to the risk of secondary hazards caused by the aftershocks. It was clear that it is necessary to use a portable warning system to issue the onsite P wave alarm. Because FREQL was originally developed as portable equipment, Tokyo Fire Department asked us to modify it to the portable equipment with the loud sound and the light signal. In this moment, this portable FREQL has equipped in nation wide. When the hyper rescue team of Tokyo Fire Department was sent to Pakistan as a task force for rescue work of the 2005 Pakistan earthquake, the portable FREQL was used as important onsite portable warning system and P wave alarms was actually issued by three times during the rescue work. Although this is one example for the actual application of portable onsite alarm, it is possible to apply the other field as the construction field. In this presentation, Portable Onsite Alarm is discussed from views of its necessity and application.

Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models.

PubMed

Chan, Ta-Chien; Teng, Yung-Chu; Hwang, Jing-Shiang

2015-02-21

Emerging novel influenza outbreaks have increasingly been a threat to the public and a major concern of public health departments. Real-time data in seamless surveillance systems such as health insurance claims data for influenza-like illnesses (ILI) are ready for analysis, making it highly desirable to develop practical techniques to analyze such readymade data for outbreak detection so that the public can receive timely influenza epidemic warnings. This study proposes a simple and effective approach to analyze area-based health insurance claims data including outpatient and emergency department (ED) visits for early detection of any aberrations of ILI. The health insurance claims data during 2004-2009 from a national health insurance research database were used for developing early detection methods. The proposed approach fitted the daily new ILI visits and monitored the Pearson residuals directly for aberration detection. First, negative binomial regression was used for both outpatient and ED visits to adjust for potentially influential factors such as holidays, weekends, seasons, temporal dependence and temperature. Second, if the Pearson residuals exceeded 1.96, aberration signals were issued. The empirical validation of the model was done in 2008 and 2009. In addition, we designed a simulation study to compare the time of outbreak detection, non-detection probability and false alarm rate between the proposed method and modified CUSUM. The model successfully detected the aberrations of 2009 pandemic (H1N1) influenza virus in northern, central and southern Taiwan. The proposed approach was more sensitive in identifying aberrations in ED visits than those in outpatient visits. Simulation studies demonstrated that the proposed approach could detect the aberrations earlier, and with lower non-detection probability and mean false alarm rate in detecting aberrations compared to modified CUSUM methods. The proposed simple approach was able to filter out temporal trends, adjust for temperature, and issue warning signals for the first wave of the influenza epidemic in a timely and accurate manner.

Linking Research to Practice: FEWS NET and Its Use of Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The purpose of the Famine Early Warning Systems Network (FEWS NET) is to collaborate with international, regional and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issues

1. View of three detection radar (DR) antennas. DR 1 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. View of three detection radar (DR) antennas. DR 1 (structure no. 735) on left, DR 2 (structure no. 736) in center, and DR 3 (structure no. 737) looking north 30 degrees west, with tracking radar (large radome) and satcom (satellite communication) system in small radome in view between DR 2 and DR 3 antennae. - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Climate Change Implications and Use of Early Warning Systems for Global Dust Storms

NASA Astrophysics Data System (ADS)

Harriman, L.

2014-12-01

Increased changes in land cover and global climate have led to increased frequency and/or intensity of dust storms in some regions of the world. Early detection and warning of dust storms, in conjunction with effective and widespread information broadcasts, will be essential to the prevention and mitigation of future risks and impacts to people and the environment. Since frequency and intensity of dust storms can vary from region to region, there is a demonstrated need for more research to be conducted over longer periods of time to analyze trends of dust storm events [1]. Dust storms impact their origin area, but also land, water and people a great distance away from where dust finally settles [2, 3]. These transboundary movements and accompanying impacts further warrant the need for global collaboration to help predict the onset, duration and path of a dust storm. Early warning systems can help communicate when a dust storm is occurring, the projected intensity of the dust storm and its anticipated physical impact over a particular geographic area. Development of regional dust storm models, such as CUACE/Dust for East Asia, and monitoring networks, like the Sand and Dust Storm Warning Network operated by the World Meteorological Organization, and the use of remote sensing and satellite imagery derived products [4], including MODIS, are currently being incorporated into early warning and monitoring initiatives. However, to increase future certainty of impacts of dust storms on vulnerable populations and ecosystems, more research is needed to analyze the influences of human activities, seasonal variations and long-term climatic patterns on dust storm generation, movement and impact. Sources: [1] Goudie, A.S. (2009), Dust storms: recent developments, J Environ. Manage., 90. [2] Lee, H., and Liu, C. (2004), Coping with dust storm events: information, impacts, and policymaking in Taiwan, TAO, 15(5). [3] Marx, S.K., McGowan, H.A., and Balz, K.S. (2009), Long-range dust transport from eastern Australia: a proxy for Holocene aridity and ENSO-type climate variability, Earth Planet Sci. Lett., 282. [4] Kimura, R. (2012), Factors contributing to dust storms in source regions producing the yellow-sand phenomena observed in Japan from 1993 to 2002, J. Arid Environ. 80

Implementation of Pediatric Early Warning Score; Adherence to Guidelines and Influence of Context.

PubMed

Almblad, Ann-Charlotte; Siltberg, Petra; Engvall, Gunn; Målqvist, Mats

To describe data of Pediatric Early Warning Score (PEWS) registrations and to evaluate the implementation of PEWS by examining adherence to clinical guidelines based on measured PEWS, and to relate findings to work context. PEWS, as a part of a concept called Early Detection and Treatment-Children (EDT-C) was implemented at three wards at a Children's Hospital in Sweden. Data were collected from the Electronic Patient Record (EPR) retrospectively to assess adherence to guidelines. The Alberta Context Tool (ACT) was used to assess work context among healthcare professionals (n=109) before implementation of EDT-C. The majority of PEWS registrations in EPR were low whereas 10% were moderate to high. Adherences to ward-specific guidelines at admission and for saturation in respiratory distress were high whereas adherence to pain assessment was low. There were significant differences in documented recommended actions between wards. Some differences in leadership and evaluation between wards were identified. Evaluation of PEWS implementation indicated frequent use of the tool despite most scores being low. High scores (5-9) occurred 28 times, which may indicate that patients with a high risk of clinical deterioration were identified. Documentation of the consequent recommended actions was however incomplete and there was a large variation in adherence to guidelines. Contextual factors may have an impact on adherence. EDT-C can lead to increased knowledge about early detection of deterioration, strengthen nurses as professionals, optimize treatment and teamwork and thereby increase patient safety for children treated in hospitals. Copyright © 2017 Elsevier Inc. All rights reserved.

Volvo and Infiniti drivers' experiences with select crash avoidance technologies.

PubMed

Braitman, Keli A; McCartt, Anne T; Zuby, David S; Singer, Jeremiah

2010-06-01

Vehicle-based crash avoidance systems can potentially reduce crashes, but success depends on driver acceptance and understanding. This study gauged driver use, experience, and acceptance among early adopters of select technologies. Telephone interviews were conducted in early 2009 with 380 owners of Volvo vehicles equipped with forward collision warning with autobrake, lane departure warning, side-view assist, and/or active bi-xenon headlights and 485 owners of Infiniti vehicles with lane departure warning/prevention. Most owners kept systems turned on most of the time, especially forward collision warning with autobrake and side-view assist. The exception was lane departure prevention; many owners were unaware they had it, and the system must be activated each time the vehicle is started. Most owners reported being safer with the technologies and would want them again on their next vehicles. Perceived false or unnecessary warnings were fairly common, particularly with side-view assist. Some systems were annoying, especially lane departure warning. Many owners reported safer driving behaviors such as greater use of turn signals (lane departure warning), increased following distance (forward collision warning), and checking side mirrors more frequently (side-view assist), but some reported driving faster at night (active headlights). Despite some unnecessary or annoying warnings, most Volvo and Infiniti owners use crash avoidance systems most of the time. Among early adopters, the first requirement of effective warning systems (that owners use the technology) seems largely met. Systems requiring activation by drivers for each trip are used less often. Owner experience with the latest technologies from other automobile manufacturers should be studied, as well as for vehicles on which technologies are standard (versus optional) equipment. The effectiveness of technologies in preventing and mitigating crashes and injuries, and user acceptance of interfaces, should be examined as more vehicles with advanced technologies penetrate the fleet.

[Reliability and validity of warning signs checklist for screening psychological, behavioral and developmental problems of children].

PubMed

Huang, X N; Zhang, Y; Feng, W W; Wang, H S; Cao, B; Zhang, B; Yang, Y F; Wang, H M; Zheng, Y; Jin, X M; Jia, M X; Zou, X B; Zhao, C X; Robert, J; Jing, Jin

2017-06-02

Objective: To evaluate the reliability and validity of warning signs checklist developed by the National Health and Family Planning Commission of the People's Republic of China (NHFPC), so as to determine the screening effectiveness of warning signs on developmental problems of early childhood. Method: Stratified random sampling method was used to assess the reliability and validity of checklist of warning sign and 2 110 children 0 to 6 years of age(1 513 low-risk subjects and 597 high-risk subjects) were recruited from 11 provinces of China. The reliability evaluation for the warning signs included the test-retest reliability and interrater reliability. With the use of Age and Stage Questionnaire (ASQ) and Gesell Development Diagnosis Scale (GESELL) as the criterion scales, criterion validity was assessed by determining the correlation and consistency between the screening results of warning signs and the criterion scales. Result: In terms of the warning signs, the screening positive rates at different ages ranged from 10.8%(21/141) to 26.2%(51/137). The median (interquartile) testing time for each subject was 1(0.6) minute. Both the test-retest reliability and interrater reliability of warning signs reached 0.7 or above, indicating that the stability was good. In terms of validity assessment, there was remarkable consistency between ASQ and warning signs, with the Kappa value of 0.63. With the use of GESELL as criterion, it was determined that the sensitivity of warning signs in children with suspected developmental delay was 82.2%, and the specificity was 77.7%. The overall Youden index was 0.6. Conclusion: The reliability and validity of warning signs checklist for screening early childhood developmental problems have met the basic requirements of psychological screening scales, with the characteristics of short testing time and easy operation. Thus, this warning signs checklist can be used for screening psychological and behavioral problems of early childhood, especially in community settings.

Optical Embedded Dust Sensor for Engine Protection and Early Warning on M1 Abrams/Ground Combat Vehicles

DTIC Science & Technology

2012-04-11

warning of seal leakage or deterioration of air filters, thereby reducing engine damage and improving vehicle operational readiness. To be effective , the...for a comprehensive early warning and health management solution. To address the need for an effective dust detector for the AGT1500 engine and M1...an optical dust sensor for real-time continuous monitoring, and its effectiveness in quantitatively measuring dust penetration in the AGT1500 engine

[System construction of early warning for ecological security at cultural and natural heritage mixed sites and its application: a case study of Wuyishan Scenery District].

PubMed

You, Wei-Bin; He, Dong-Jin; Qin, De-Hua; Ji, Zhi-Rong; Wu, Li-Yun; Yu, Jian-An; Chen, Bing-Rong; Tan, Yong

2014-05-01

This paper proposed a new concept of ecological security for protection by a comprehensive analysis of the contents and standards of world heritage sites. A frame concept model named "Pressure-State-Control" for early warning of ecological security at world heritage mixed sites was constructed and evaluation indicators of this frame were also selected. Wuyishan Scenery District was chosen for a case study, which has been severely disturbed by natural and artificial factors. Based on the frame model of "Pressure-State-Control" and by employing extension analysis, the matter-element model was established to assess the ecological security status of this cultural and natural world heritage mixed site. The results showed that the accuracy of ecological security early warning reached 84%. Early warning rank was I level (no alert status) in 1997 and 2009, but that in 2009 had a higher possibility to convert into II level. Likewise, the early-warning indices of sensitive ranks were different between 1997 and 2009. Population density, population growth rate, area index for tea garden, cultivated land owned per capita, level of drought, and investment for ecological and environmental construction were the main limiting factors to hinder the development of ecological security from 2009 to future. In general, the status of Wuyishan Scenery District ecological security was relatively good and considered as no alert level, while risk conditions also existed in terms of a few early-warning indicators. We still need to pay more attention to serious alert indicators and adopt effective prevention and control measures to maintain a good ecological security status of this heritage site.

Refuting the ticagrelor-aspirin black box warning: and proposing a ticagrelor early-PCI black box warning.

PubMed

DiNicolantonio, James J; Serebruany, Victor L; Tomek, Ales

2013-10-03

Ticagrelor, a novel reversible antiplatelet agent, has a black box warning to avoid maintenance doses of aspirin>100mg. However, a significant ticagrelor-early percutaneous coronary intervention (PCI) interaction exists. To discuss the inappropriateness of the black box warning for aspirin doses>100mg with ticagrelor and the appropriateness (and need) for a black box warning for ticagrelor patients needing early (within 24 hours of randomization) PCI. The FDA Complete Response Review for ticagrelor indicates that aspirin doses ≥ 300 mg/daily was not a significant interaction. In the ticagrelor-aspirin ≥ 300 mg cohort, all-cause mortality (through study end) and cardiovascular (CV) mortality (through study end) were not significantly increased (HR=1.27; 95% CI, 0.84-1.93, p=0.262 and HR=1.39; 95% CI:0.87-2.2, p=0.170), respectively. However, in patients treated with early (within 24 hours) PCI, ticagrelor significantly increased all-cause mortality (30 day: HR=1.89; 95% CI: 1.26-2.81, p=0.002, and through study end, HR=1.41; 95% CI,1.08-1.84, p=0.012) and increased CV mortality (30 day: HR=1.31; 95% CI: 0.97-1.77, p=0.075, and through study end, HR=1.35; 95% CI, 0.995-1.82, p=0.054) compared to clopidogrel. Early-PCI was more prevalent in the US versus outside-US regions (61% versus 49%). The black box warning for the use of maintenance aspirin doses over 100mg/daily with ticagrelor is inappropriate and ignores the more important, credible, and highly significant ticagrelor-early PCI adverse interaction in PLATO. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Small-scale (flash) flood early warning in the light of operational requirements: opportunities and limits with regard to user demands, driving data, and hydrologic modeling techniques

NASA Astrophysics Data System (ADS)

Philipp, Andy; Kerl, Florian; Büttner, Uwe; Metzkes, Christine; Singer, Thomas; Wagner, Michael; Schütze, Niels

2016-05-01

In recent years, the Free State of Saxony (Eastern Germany) was repeatedly hit by both extensive riverine flooding, as well as flash flood events, emerging foremost from convective heavy rainfall. Especially after a couple of small-scale, yet disastrous events in 2010, preconditions, drivers, and methods for deriving flash flood related early warning products are investigated. This is to clarify the feasibility and the limits of envisaged early warning procedures for small catchments, hit by flashy heavy rain events. Early warning about potentially flash flood prone situations (i.e., with a suitable lead time with regard to required reaction-time needs of the stakeholders involved in flood risk management) needs to take into account not only hydrological, but also meteorological, as well as communication issues. Therefore, we propose a threefold methodology to identify potential benefits and limitations in a real-world warning/reaction context. First, the user demands (with respect to desired/required warning products, preparation times, etc.) are investigated. Second, focusing on small catchments of some hundred square kilometers, two quantitative precipitation forecasts are verified. Third, considering the user needs, as well as the input parameter uncertainty (i.e., foremost emerging from an uncertain QPF), a feasible, yet robust hydrological modeling approach is proposed on the basis of pilot studies, employing deterministic, data-driven, and simple scoring methods.

An Offshore Geophysical Network in the Pacific Northwest for Earthquake and Tsunami Early Warning and Hazard Research

NASA Astrophysics Data System (ADS)

Wilcock, W. S. D.; Schmidt, D. A.; Vidale, J. E.; Harrington, M.; Bodin, P.; Cram, G.; Delaney, J. R.; Gonzalez, F. I.; Kelley, D. S.; LeVeque, R. J.; Manalang, D.; McGuire, C.; Roland, E. C.; Tilley, J.; Vogl, C. J.; Stoermer, M.

2016-12-01

The Cascadia subduction zone hosts catastrophic earthquakes every few hundred years. On land, there are extensive geophysical networks available to monitor the subduction zone, but since the locked portion of the plate boundary lies mostly offshore, these networks are ideally complemented by seafloor observations. Such considerations helped motivate the development of scientific cabled observatories that cross the subduction zone at two sites off Vancouver Island and one off central Oregon, but these have a limited spatial footprint along the strike of the subduction zone. The Pacific Northwest Seismic Network is leading a collaborative effort to implement an earthquake early warning system in the Washington and Oregon using data streams from land networks as well as the few existing offshore instruments. For subduction zone earthquakes that initiate offshore, this system will provide a warning. However, the availability of real time offshore instrumentation along the entire subduction zone would improve its reliability and accuracy, add up to 15 s to the warning time, and ensure an early warning for coastal communities near the epicenter. Furthermore, real-time networks of seafloor pressure sensors above the subduction zone would enable monitoring and contribute to accurate predictions of the incoming tsunami. There is also strong scientific motivation for offshore monitoring. We lack a complete knowledge of the plate convergence rate and direction. Measurements of steady deformation and observations of transient processes such as fluid pulsing, microseismic cycles, tremor and slow-slip are necessary for assessing the dimensions of the locked zone and its along-strike segmentation. Long-term monitoring will also provide baseline observations that can be used to detect and evaluate changes in the subduction environment. There are significant engineering challenges to be solved to ensure the system is sufficiently reliable and maintainable. It must provide continuous monitoring over its operational life in the harsh ocean environment and at least parts of the system must continue to operate following a megathrust event. These requirements for robustness must be balanced with the desire for a flexible design that can accommodate new scientific instrumentation over the life of the project.

7 Warning Signs of Alzheimer's | Alzheimer's disease | NIH MedlinePlus the Magazine

MedlinePlus

... please turn Javascript on. Feature: Alzheimer's Disease 7 Warning Signs of Alzheimer's Past Issues / Fall 2010 Table ... is to alert the public to the early warning signs of Alzheimer's disease. If someone has several ...

Educator Evaluation and the Use of the Early Warning Indicator System (EWIS). Updated September 9, 2013

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education first released the Early Warning Indicator System (EWIS) data for grades 1-12 in the 2012-13 school year. The Department created the EWIS in direct response to educators' requests for early indicator data across multiple grade levels. The EWIS is a "tool to systematically…

Theory and Application of Early Warning Systems for High School and Beyond

ERIC Educational Resources Information Center

Carl, Bradley; Richardson, Jed T.; Cheng, Emily; Kim, HeeJin; Meyer, Robert H.

2013-01-01

This article describes the development of early warning indicators for high school and beyond in the Milwaukee Public Schools (MPS) by the Value-Added Research Center (VARC) at the University of Wisconsin-Madison, working in conjunction with staff from the Division of Research and Evaluation at MPS. Our work in MPS builds on prior early warning…

ON-LINE TOXICITY MONITORS AND WATERSHED EARLY WARNING SYSTEMS

EPA Science Inventory

A Water Quality Early Warning System using On-line Toxicity Monitors (OTMs) has been deployed in the East Fork of the Little Miami River, Clermont County, OH. Living organisms have long been used to determine the toxicity of environmental samples. With advancements in electronic ...

IG Statement: Arthur A. Elkins, Jr., on OIG report Early Warning Report: Main EPA Headquarters Warehouse in Landover, Maryland, Requires Immediate EPA Attention

EPA Pesticide Factsheets

Statement of Inspector General Arthur A. Elkins, Jr., on the Office of Inspector General (OIG) report Early Warning Report: Main EPA Headquarters Warehouse in Landover, Maryland, Requires Immediate EPA Attention.

Multiple-Threshold Event Detection and Other Enhancements to the Virtual Seismologist (VS) Earthquake Early Warning Algorithm

NASA Astrophysics Data System (ADS)

Fischer, M.; Caprio, M.; Cua, G. B.; Heaton, T. H.; Clinton, J. F.; Wiemer, S.

2009-12-01

The Virtual Seismologist (VS) algorithm is a Bayesian approach to earthquake early warning (EEW) being implemented by the Swiss Seismological Service at ETH Zurich. The application of Bayes’ theorem in earthquake early warning states that the most probable source estimate at any given time is a combination of contributions from a likelihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS algorithm was one of three EEW algorithms involved in the California Integrated Seismic Network (CISN) real-time EEW testing and performance evaluation effort. Its compelling real-time performance in California over the last three years has led to its inclusion in the new USGS-funded effort to develop key components of CISN ShakeAlert, a prototype EEW system that could potentially be implemented in California. A significant portion of VS code development was supported by the SAFER EEW project in Europe. We discuss recent enhancements to the VS EEW algorithm. We developed and continue to test a multiple-threshold event detection scheme, which uses different association / location approaches depending on the peak amplitudes associated with an incoming P pick. With this scheme, an event with sufficiently high initial amplitudes can be declared on the basis of a single station, maximizing warning times for damaging events for which EEW is most relevant. Smaller, non-damaging events, which will have lower initial amplitudes, will require more picks to be declared an event to reduce false alarms. This transforms the VS codes from a regional EEW approach reliant on traditional location estimation (and it requirement of at least 4 picks as implemented by the Binder Earthworm phase associator) to a hybrid on-site/regional approach capable of providing a continuously evolving stream of EEW information starting from the first P-detection. Offline analysis on Swiss and California waveform datasets indicate that the multiple-threshold approach is faster and more reliable for larger events than the earlier version of the VS codes. This multiple-threshold approach is well-suited for implementation on a wide range of devices, from embedded processor systems installed at a seismic stations, to small autonomous networks for local warnings, to large-scale regional networks such as the CISN. In addition, we quantify the influence of systematic use of prior information and Vs30-based corrections for site amplification on VS magnitude estimation performance, and describe how components of the VS algorithm will be integrated into non-EEW standard network processing procedures at CHNet, the national broadband / strong motion network in Switzerland. These enhancements to the VS codes will be transitioned from off-line to real-time testing at CHNet in Europe in the coming months, and will be incorporated into the development of key components of CISN ShakeAlert prototype system in California.

Including trait-based early warning signals helps predict population collapse

PubMed Central

Clements, Christopher F.; Ozgul, Arpat

2016-01-01

Foreseeing population collapse is an on-going target in ecology, and this has led to the development of early warning signals based on expected changes in leading indicators before a bifurcation. Such signals have been sought for in abundance time-series data on a population of interest, with varying degrees of success. Here we move beyond these established methods by including parallel time-series data of abundance and fitness-related trait dynamics. Using data from a microcosm experiment, we show that including information on the dynamics of phenotypic traits such as body size into composite early warning indices can produce more accurate inferences of whether a population is approaching a critical transition than using abundance time-series alone. By including fitness-related trait information alongside traditional abundance-based early warning signals in a single metric of risk, our generalizable approach provides a powerful new way to assess what populations may be on the verge of collapse. PMID:27009968

[Early warning on measles through the neural networks].

PubMed

Yu, Bin; Ding, Chun; Wei, Shan-bo; Chen, Bang-hua; Liu, Pu-lin; Luo, Tong-yong; Wang, Jia-gang; Pan, Zhi-wei; Lu, Jun-an

2011-01-01

To discuss the effects on early warning of measles, using the neural networks. Based on the available data through monthly and weekly reports on measles from January 1986 to August 2006 in Wuhan city. The modal was developed using the neural networks to predict and analyze the prevalence and incidence of measles. When the dynamic time series modal was established with back propagation (BP) networks consisting of two layers, if p was assigned as 9, the convergence speed was acceptable and the correlation coefficient was equal to 0.85. It was more acceptable for monthly forecasting the specific value, but better for weekly forecasting the classification under probabilistic neural networks (PNN). When data was big enough to serve the purpose, it seemed more feasible for early warning using the two-layer BP networks. However, when data was not enough, then PNN could be used for the purpose of prediction. This method seemed feasible to be used in the system for early warning.

Early warning indicators for monitoring the process failure of anaerobic digestion system of food waste.

PubMed

Li, Lei; He, Qingming; Wei, Yunmei; He, Qin; Peng, Xuya

2014-11-01

To determine reliable state parameters which could be used as early warning indicators of process failure due to the acidification of anaerobic digestion of food waste, three mesophilic anaerobic digesters of food waste with different operation conditions were investigated. Such parameters as gas production, methane content, pH, concentrations of volatile fatty acid (VFA), alkalinity and their combined indicators were evaluated. Results revealed that operation conditions significantly affect the responses of parameters and thus the optimal early warning indicators of each reactor differ from each other. None of the single indicators was universally valid for all the systems. The universally valid indicators should combine several parameters to supply complementary information. A combination of total VFA, the ratio of VFA to total alkalinity (VFA/TA) and the ratio of bicarbonate alkalinity to total alkalinity (BA/TA) can reflect the metabolism of the digesting system and realize rapid and effective early warning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Early warnings of the potential for malaria transmission in Rural Africa using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS)

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Eltahir, E. A.

2010-12-01

Early warnings of malaria transmission allow health officials to better prepare for future epidemics. Monitoring rainfall is recognized as an important part of malaria early warning systems, as outlined by the Roll Back Malaria Initiative. The Hydrology, Entomology and Malaria Simulator (HYDREMATS) is a mechanistic model that relates rainfall to malaria transmission, and could be used to provide early warnings of malaria epidemics. HYDREMATS is used to make predictions of mosquito populations and vectorial capacity for 2005, 2006, and 2007 in Banizoumbou village in western Niger. HYDREMATS is forced by observed rainfall, followed by a rainfall prediction based on the seasonal mean rainfall for a period two or four weeks into the future. Predictions made using this method provided reasonable estimates of mosquito populations and vectorial capacity, two to four weeks in advance. The predictions were significantly improved compared to those made when HYDREMATS was forced with seasonal mean rainfall alone.

Suitability of Open-Ocean Instrumentation for Use in Near-Field Tsunami Early Warning Along Seismically Active Subduction Zones

NASA Astrophysics Data System (ADS)

Williamson, Amy L.; Newman, Andrew V.

2018-05-01

Over the past decade, the number of open-ocean gauges capable of parsing information about a passing tsunami has steadily increased, particularly through national cable networks and international buoyed efforts such as the Deep-ocean Assessment and Reporting of Tsunami (DART). This information is analyzed to disseminate tsunami warnings to affected regions. However, most current warnings that incorporate tsunami are directed at mid- and far-field localities. In this study, we analyze the region surrounding four seismically active subduction zones, Cascadia, Japan, Chile, and Java, for their potential to facilitate local tsunami early warning using such systems. We assess which locations currently have instrumentation in the right locations for direct tsunami observations with enough time to provide useful warning to the nearest affected coastline—and which are poorly suited for such systems. Our primary findings are that while some regions are ill-suited for this type of early warning, such as the coastlines of Chile, other localities, like Java, Indonesia, could incorporate direct tsunami observations into their hazard forecasts with enough lead time to be effective for coastal community emergency response. We take into account the effect of tsunami propagation with regard to shallow bathymetry on the fore-arc as well as the effect of earthquake source placement. While it is impossible to account for every type of off-shore tsunamigenic event in these locales, this study aims to characterize a typical large tsunamigenic event occurring in the shallow part of the megathrust as a guide in what is feasible with early tsunami warning.

Food Security, Decision Making and the Use of Remote Sensing in Famine Early Warning Systems

NASA Technical Reports Server (NTRS)

Brown, Molly E.

2008-01-01

Famine early warning systems use remote sensing in combination with socio-economic and household food economy analysis to provide timely and rigorous information on emerging food security crises. The Famine Early Warning Systems Network (FEWS NET) is the US Agency for International Development's decision support system in 20 African countries, as well as in Guatemala, Haiti and Afghanistan. FEWS NET provides early and actionable policy guidance for the US Government and its humanitarian aid partners. As we move into an era of climate change where weather hazards will become more frequent and severe, understanding how to provide quantitative and actionable scientific information for policy makers using biophysical data is critical for an appropriate and effective response.

a Process-Based Drought Early Warning Indicator for Supporting State Drought Mitigation Decision

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, D. N.; Pu, B.

2014-12-01

Drought prone states such as Texas requires creditable and actionable drought early warning ranging from seasonal to multi-decadal scales. Such information cannot be simply extracted from the available climate prediction and projections because of their large uncertainties at regional scales and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA national multi-models ensemble experiment (NMME) and the IPCC AR5 (CMIP5) models, are much more reliable for winter and spring than for the summer season for the US Southern Plains. They also show little connection between the droughts in winter/spring and those in summer, in contrast to the observed dry memory from spring to summer over that region. To mitigate the weakness of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies. Based on these key processes and related fields, we have developed a multivariate principle component statistical model to provide a probabilistic summer drought early warning indicator, using the observed or predicted climate conditions in winter and spring on seasonal scale and climate projection for the mid-21stcentury. The summer drought early warning indicator is constructed in a similar way to the NOAA probabilistic predictions that are familiar to water resource managers. The indicator skill is assessed using the standard NOAA climate prediction assessment tools, i.e., the two alternative forced choice (2AFC) and the Receiver Operating Characteristic (ROC). Comparison with long-term observations suggest that this summer drought early warning indicator is able to capture nearly all the strong summer droughts and outperform the dynamic prediction in this regard over the US Southern Plains. This early warning indicator has been used by the state water agency in May 2014 in briefing the state drought preparedness council and will be provided to stake holders through the website of the Texas state water planning agency. We will also present the results of our ongoing work on using NASA satellite based soil moisture and vegetation stress measurements to further improve the reliability of the summer drought early warning indicator.

Detecting early signs of the 2007–2008 crisis in the world trade

PubMed Central

Saracco, Fabio; Di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-01-01

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008–2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995–2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles. PMID:27461469

Detecting early signs of the 2007-2008 crisis in the world trade.

PubMed

Saracco, Fabio; Di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-07-27

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.

Detecting early signs of the 2007-2008 crisis in the world trade

NASA Astrophysics Data System (ADS)

Saracco, Fabio; di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-07-01

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.

2007 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-07-31

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 East Tennessee Technology Park Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2009-07-13

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Lawrence Livermore National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-08-16

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Nevada National Security Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-07-28

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Oak Ridge National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-16

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Brookhaven National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-03-06

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Y-12 National Security Complex Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-04-17

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 East Tennessee Technology Park Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-08-16

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Los Alamos National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-06-13

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Oak Ridge National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-07-28

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Idaho National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2009-05-04

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2007 Lawrence Livermore National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-05-20

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2010 Y-12 National Security Complex Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2011-08-31

The U.S. Department of Energy's (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Lawrence Livermore National Laboratory Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-03-27

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Savannah River Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-08-20

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Nevada Test Site Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-04-24

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

2006 Kansas City Plant Annual Illness and Injury Surveillance Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

U.S. Department of Energy, Office of Health, Safety and Health, Office of Health and Safety, Office of Illness and Injury Prevention Programs

2008-06-13

The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

Sun-Burned: Space Weather’s Impact On U.S. National Security

DTIC Science & Technology

2013-06-01

for navigation, the wideband global satellite communications system used for secure links in multiple frequencies , the space-based infrared system...used for early warning missile detection, the advanced extremely high frequency used for jam resistant strategic communications , and the defense...NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11 . SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for

Research on intelligent scenic security early warning platform based on high resolution image: real scene linkage and real-time LBS

NASA Astrophysics Data System (ADS)

Li, Baishou; Huang, Yu; Lan, Guangquan; Li, Tingting; Lu, Ting; Yao, Mingxing; Luo, Yuandan; Li, Boxiang; Qian, Yongyou; Gao, Yujiu

2015-12-01

This paper design and implement security monitor system within a scenic spot for tourists, the scenic spot staff can be automatic real time for visitors to perception and monitoring, and visitors can also know about themselves location in the scenic, real-time and obtain the 3D imaging conditions of scenic area. Through early warning can realize "parent-child relation", preventing the old man and child lost and wandering. Research results to the further development of virtual reality to provide effective security early warning platform of the theoretical basis and practical reference.

Value of syndromic surveillance within the Armed Forces for early warning during a dengue fever outbreak in French Guiana in 2006

PubMed Central

Meynard, Jean-Baptiste; Chaudet, Hervé; Texier, Gaetan; Ardillon, Vanessa; Ravachol, Françoise; Deparis, Xavier; Jefferson, Henry; Dussart, Philippe; Morvan, Jacques; Boutin, Jean-Paul

2008-01-01

Background A dengue fever outbreak occured in French Guiana in 2006. The objectives were to study the value of a syndromic surveillance system set up within the armed forces, compared to the traditional clinical surveillance system during this outbreak, to highlight issues involved in comparing military and civilian surveillance systems and to discuss the interest of syndromic surveillance for public health response. Methods Military syndromic surveillance allows the surveillance of suspected dengue fever cases among the 3,000 armed forces personnel. Within the same population, clinical surveillance uses several definition criteria for dengue fever cases, depending on the epidemiological situation. Civilian laboratory surveillance allows the surveillance of biologically confirmed cases, within the 200,000 inhabitants. Results It was shown that syndromic surveillance detected the dengue fever outbreak several weeks before clinical surveillance, allowing quick and effective enhancement of vector control within the armed forces. Syndromic surveillance was also found to have detected the outbreak before civilian laboratory surveillance. Conclusion Military syndromic surveillance allowed an early warning for this outbreak to be issued, enabling a quicker public health response by the armed forces. Civilian surveillance system has since introduced syndromic surveillance as part of its surveillance strategy. This should enable quicker public health responses in the future. PMID:18597694

European Neolithic societies showed early warning signals of population collapse

PubMed Central

Downey, Sean S.; Haas, W. Randall; Shennan, Stephen J.

2016-01-01

Ecosystems on the verge of major reorganization—regime shift—may exhibit declining resilience, which can be detected using a collection of generic statistical tests known as early warning signals (EWSs). This study explores whether EWSs anticipated human population collapse during the European Neolithic. It analyzes recent reconstructions of European Neolithic (8–4 kya) population trends that reveal regime shifts from a period of rapid growth following the introduction of agriculture to a period of instability and collapse. We find statistical support for EWSs in advance of population collapse. Seven of nine regional datasets exhibit increasing autocorrelation and variance leading up to collapse, suggesting that these societies began to recover from perturbation more slowly as resilience declined. We derive EWS statistics from a prehistoric population proxy based on summed archaeological radiocarbon date probability densities. We use simulation to validate our methods and show that sampling biases, atmospheric effects, radiocarbon calibration error, and taphonomic processes are unlikely to explain the observed EWS patterns. The implications of these results for understanding the dynamics of Neolithic ecosystems are discussed, and we present a general framework for analyzing societal regime shifts using EWS at large spatial and temporal scales. We suggest that our findings are consistent with an adaptive cycling model that highlights both the vulnerability and resilience of early European populations. We close by discussing the implications of the detection of EWS in human systems for archaeology and sustainability science. PMID:27573833

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis.

PubMed

Yang, Tsung-Ming; Fan, Shu-Kai; Fan, Chihhao; Hsu, Nien-Sheng

2014-08-01

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.

SSME leak detection feasibility investigation by utilization of infrared sensor technology

NASA Technical Reports Server (NTRS)

Shohadaee, Ahmad A.; Crawford, Roger A.

1990-01-01

This investigation examined the potential of using state-of-the-art technology of infrared (IR) thermal imaging systems combined with computer, digital image processing and expert systems for Space Shuttle Main Engines (SSME) propellant path peak detection as an early warning system of imminent engine failure. A low-cost, laboratory experiment was devised and an experimental approach was established. The system was installed, checked out, and data were successfully acquired demonstrating the proof-of-concept. The conclusion from this investigation is that both numerical and experimental results indicate that the leak detection by using infrared sensor technology proved to be feasible for a rocket engine health monitoring system.

Global situational awareness and early warning of high-consequence climate change.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Backus, George A.; Carr, Martin J.; Boslough, Mark Bruce Elrick

2009-08-01

Global monitoring systems that have high spatial and temporal resolution, with long observational baselines, are needed to provide situational awareness of the Earth's climate system. Continuous monitoring is required for early warning of high-consequence climate change and to help anticipate and minimize the threat. Global climate has changed abruptly in the past and will almost certainly do so again, even in the absence of anthropogenic interference. It is possible that the Earth's climate could change dramatically and suddenly within a few years. An unexpected loss of climate stability would be equivalent to the failure of an engineered system on amore » grand scale, and would affect billions of people by causing agricultural, economic, and environmental collapses that would cascade throughout the world. The probability of such an abrupt change happening in the near future may be small, but it is nonzero. Because the consequences would be catastrophic, we argue that the problem should be treated with science-informed engineering conservatism, which focuses on various ways a system can fail and emphasizes inspection and early detection. Such an approach will require high-fidelity continuous global monitoring, informed by scientific modeling.« less

Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

PubMed Central

Hübl, Johannes; McArdell, Brian W.; Walter, Fabian

2018-01-01

The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449

Satellite detection, tracing, and early warning of harmful algal blooms (HABs) for the Asian waters

NASA Astrophysics Data System (ADS)

Tang, D. L.

Over the past two decades, Harmful Algal Blooms (HABs) appear to have increased in frequency, intensity and geographic distribution worldwide, and have caused large economic losses in aquacultured and wild fisheries in recent years. Understanding of the oceanic mechanisms is important for early warning of HAB events. The present study reported several extensive HABs in the Asian waters during 1998 to 2003 detected by satellite remote sensing data (SeaWiFS, NOAA AVHRR, and QuikScat) and in situ observations. An extensive HAB off southeastern Vietnamese waters during late June to July 2002 was detected and its related oceanographic features were analyzed. The HAB had high Chlorophyll-a (Chl-a) concentrations (up to 4.5 mg m-3), occurring about 200 km off the coast and about 200 km northeast of the Mekong River mouth, for a period of about 6 weeks. The bloom was dominated by the harmful algae haptophyte Phaeocystis cf. globosa, and caused a very significant mortality of aquacultured fishes and other marine life. In the same period, Sea Surface Temperature (SST) imagery showed a coldwater plume extending from the coast to the open sea, and QuikScat data showed strong southwesterly winds blowing parallel with the coastline. It indicated the HAB was induced and supported by offshore upwelling that bring nutrients from the deep ocean to the surface and from coastal water to the offshore, and the upwelling was driven by strong wind through Ekman transport when winds were parallel with the coastline. This study demonstrated the possibility of utilizing a combination of satellite data of Chl-a, SST and wind velocity together with coastal bathymetric information and in situ observation to give a better understanding of the biological oceanography of HABs; these results may help for the early warming of HAB.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

NASA Astrophysics Data System (ADS)

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-12-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

PubMed Central

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-01-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.

PubMed

Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M

2014-12-08

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Implementing an Inpatient Social Early Warning System for Child Maltreatment

ERIC Educational Resources Information Center

Atabaki, Armita; Heddaeus, Daniela; Metzner, Franka; Schulz, Holger; Siefert, Sonke; Pawils, Silke

2013-01-01

Objectives: The current article describes the process evaluation of a social early warning system (SEWS) for the prevention of child maltreatment in the federal state of Hamburg. This prevention initiative targets expectant mothers and their partners including an initial screening of risk factors for child maltreatment, a subsequent structured…

Improving Early Warning Systems with Categorized Course Resource Usage

ERIC Educational Resources Information Center

Waddington, R. Joseph; Nam, SungJin; Lonn, Steven; Teasley, Stephanie D.

2016-01-01

Early Warning Systems (EWSs) aggregate multiple sources of data to provide timely information to stakeholders about students in need of academic support. There is an increasing need to incorporate relevant data about student behaviors into the algorithms underlying EWSs to improve predictors of students' success or failure. Many EWSs currently…

78 FR 68831 - Agency Information Collection Activities; Submission to the Office of Management and Budget for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-15

... Early Warning and Intervention Monitoring System AGENCY: Institute of Education Sciences/National Center... Intervention Monitoring System. OMB Control Number: 1850-NEW. Type of Review: New collection. Respondents... planning a two-part evaluation of the Early Warning and Intervention Monitoring System (EWIMS), consisting...

78 FR 48863 - Agency Information Collection Activities; Comment Request; Evaluation of the Early Warning and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-12

... DEPARTMENT OF EDUCATION [Docket No.: ED-2013-ICCD-0106] Agency Information Collection Activities; Comment Request; Evaluation of the Early Warning and Intervention Monitoring System AGENCY: Institute of... Intervention Monitoring System. OMB Control Number: 1850-NEW. Type of Review: A new information collection...

GPS-TEC of the Ionospheric Disturbances as a Tool for Early Tsunami Warning

NASA Astrophysics Data System (ADS)

Kunitsyn, Viacheslav E.; Nesterov, Ivan A.; Shalimov, Sergey L.; Krysanov, Boris Yu.; Padokhin, Artem M.; Rekenthaler, Douglas

2013-04-01

Recently, the GPS measurements were used for retrieving the information on the various types of ionospheric responses to seismic events (earthquakes, seismic Rayleigh waves, and tsunami) which generate atmospheric waves propagating up to the ionospheric altitudes where the collisions between the neutrals and charge particles give rise to the motion of the ionospheric plasma. These experimental results can well be used in architecture of the future tsunami warning system. The point is an earlier (in comparison with seismological methods) detection of the ionospheric signal that can indicate the moment of tsunami generation. As an example we consider the two-dimensional distributions of the vertical total electron content (TEC) variations in the ionosphere both close to and far from the epicenter of the Japan undersea earthquake of March 11, 2011 using radio tomographic (RT) reconstruction of high-temporal-resolution (2-minute) data from the Japan and the US GPS networks. Near-zone TEC variations shows a diverging ionospheric perturbation with multi-component spectral composition emerging after the main shock. The initial phase of the disturbance can be used as an indicator of the tsunami generation and subsequently for the tsunami early warning. Far-zone TEC variations reveals distinct wave train associated with gravity waves generated by tsunami. According to observations tsunami arrives at Hawaii and further at the coast of Southern California with delay relative to the gravity waves. Therefore the gravity wave pattern can be used in the early tsunami warning. We support this scenario by the results of modeling with the parameters of the ocean surface perturbation corresponding to the considered earthquake. In addition it was observed in the modeling that at long distance from the source the gravity wave can pass ahead of the tsunami. The work was supported by the Russian Foundation for Basic Research (grants 11-05-01157 and 12-05-33065).

Real-time earthquake data feasible

NASA Astrophysics Data System (ADS)

Bush, Susan

Scientists agree that early warning devices and monitoring of both Hurricane Hugo and the Mt. Pinatubo volcanic eruption saved thousands of lives. What would it take to develop this sort of early warning and monitoring system for earthquake activity?Not all that much, claims a panel assigned to study the feasibility, costs, and technology needed to establish a real-time earthquake monitoring (RTEM) system. The panel, drafted by the National Academy of Science's Committee on Seismology, has presented its findings in Real-Time Earthquake Monitoring. The recently released report states that “present technology is entirely capable of recording and processing data so as to provide real-time information, enabling people to mitigate somewhat the earthquake disaster.” RTEM systems would consist of two parts—an early warning system that would give a few seconds warning before severe shaking, and immediate postquake information within minutes of the quake that would give actual measurements of the magnitude. At this time, however, this type of warning system has not been addressed at the national level for the United States and is not included in the National Earthquake Hazard Reduction Program, according to the report.

Development of Early Warning System Using ALOS-2/PALSAR-2 Data to Detect and Prevent Deforestation

NASA Astrophysics Data System (ADS)

Hayashi, M.; Nagatani, I.; Watanabe, T.; Tadono, T.; Miyoshi, H.; Watanabe, M.; Koyama, C.; Shimada, M.; Ogawa, T.; Ishii, K.; Higashiuwatoko, T.; Miura, M.; Okonogi, H.; Adachi, K.; Morita, T.

2017-12-01

Satellite observation is an efficient method for monitoring deforestation, and a synthetic aperture radar (SAR) is useful especially in cloudy tropical forest regions. In this context, JICA and JAXA cooperate to operate the deforestation monitoring system acquired data by the Phased Array type L-band SAR-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), which is named as "JICA-JAXA Forest Early Warning System in the Tropics" (JJ-FAST), and it have been released on November 2016. JJ-FAST detects deforestation areas, and provides their positional information for 77 countries, which is covering almost all tropical forests. It uses PALSAR-2 ScanSAR observation mode (wide-observation swath width) image, which is 50 m spatial resolution acquired at 1.5 months interval. The dark change areas compared with in two acquisitions by PALSAR-2 HV-polarization images are identified as deforestations in the system. We conducted field surveys to validate detection accuracy of the JJ-FAST in Peru (November and December, 2016), Botswana (April, 2017), and Gabon (July, 2017). As the results, 15 of 18 detected areas were correct deforestation areas, therefore user's accuracy could be confirmed as 83.3 % from limited number of the validation data. Erroneous detection areas were caused by seasonal change in agricultural land and open burning in grass land. For improvement of the accuracy, such areas must be excluded from the analysis by additional algorithms e.g. estimation of accurate masking for non-forested areas. Therefore, we are revising the forest map used for pre-processing step in the system. The JJ-FAST can be expected to contribute to monitor and reduce illegal deforestation activities in tropical forests.

A narrative synthesis of factors that affect women speaking up about early warning signs and symptoms of pre-eclampsia and responses of healthcare staff.

PubMed

Carter, Wendy; Bick, Debra; Mackintosh, Nicola; Sandall, Jane

2017-02-13

One of the challenges for treating pre-eclampsia and preventing further deterioration is determining how best to enable early detection. If women or their partners and families are able to raise early warnings about potential signs and symptoms of pre-eclampsia in pregnancy, birth and in the postnatal period, women may be able to receive earlier intervention to prevent severe pre-eclampsia from developing. The aim of this study was to improve understanding of factors affecting the ability of women to recognise symptoms and signs of pre-eclampsia/eclampsia and seek appropriate medical help and factors affecting health care professionals' responses to women and their families who 'speak up' about early warning signs and symptoms. A narrative synthesis was conducted of evidence relevant to address the research question. The following electronic data bases were searched for qualitative studies which met inclusion criteria from January 1980 to April 2016; Medline, CINAHL, HMIC, PsycINFO, Embase, BNI, ASSIA, Scopus, Maternity and Infant Care, Web of Science, Google Scholar, Cochrane, JBI and IBSS with the support of an Information Service Consultant. Following thematic analysis, three themes were identified; 1: Women's understanding and knowledge of pre-eclampsia/eclampsia; 2: Factors affecting help seeking behaviour from perspectives of women and their families'; 3: Factors affecting staff response. There was widespread lack of knowledge and understanding of signs and symptoms of pre-eclampsia/eclampsia among women and their families, with some women not exhibiting signs and symptoms of pre-eclampsia or unable to distinguish them from 'normal' pregnancy changes. Women and their families not only need to be made aware of signs and symptoms of pre-eclampsia/eclampsia but also require information on the most effective ways to seek urgent medical assessment and care. Some women did not experience prodromal signs and symptoms, which raises concerns about how women and families can detect early onset, and is an issue which needs further exploration. There is very limited research exploring clinical staff response to women who raise concerns about their health when experiencing symptoms and signs of pre-eclampsia/eclampsia with further research needed if safety and quality of care are to be improved.

Glacial Lake Outburst Flood Risk in Nepal and Their Mitigation Practices in Nepal

NASA Astrophysics Data System (ADS)

Gurung, S.

2017-12-01

Glacial lakes in Nepal face a huge risk of Glacial Lake Outburst Flood (GLOF) due to the ongoing effects of climate change leading to considerable amount of snow and glacier melt thus weakening the natural barriers holding these high altitude glacial lakes. Nepal is at an ever growing risk every year and always waiting for an inevitable natural disaster. Since GLOF can cause extreme huge loss of human lives and physical properties, it has now become very important to design a proper mechanism which helps in reducing hazards from such events. There is little we can do to stop natural disasters, but we can implement pro-active control measures to minimize the loss. Early Warning System is the provision of timely and effective information, which allows individuals exposed to hazards to take action, avoid or reduce risk to life and property and prepare for effective response. The basic idea behind Early Warning System is that, the earlier and more accurately we are able to predict potential risks associated with natural hazards especially flood, the more likely we will be able to manage and mitigate the disasters' impact on society, economies and environment. We are currently focused on the development of early warning system for Imja Glacial Lake. The objective of developing early warning system for Imja GLOF is to help reduce economic losses and mitigate the number of injuries or deaths by providing information that allows individuals and communities downstream of Imja Lake to protect their lives and properties by using the latest and most advanced technology available. We have installed one Automatic Weather Station near the left lateral moraine of Imja Lake to study the effects of different meteorological parameters so as to predict occurrence of any GLOF event. The sensor includes pluviometer, pyranometer, temperature and humidity sensor, wind sensor, Snowdepth sensor. Two radar level sensors are installed at the outlet of Imja Lake and downstream of Imja river for water level measurement. Also, ten movements and volumetric water content sensors are installed to detect occurrence of any GLOF event.

Concept, Implementation and Testing of PRESTo: Real-time experimentation in Southern Italy and worldwide applications

NASA Astrophysics Data System (ADS)

Zollo, Aldo; Emolo, Antonio; Festa, Gaetano; Picozzi, Matteo; Elia, Luca; Martino, Claudio; Colombelli, Simona; Brondi, Piero; Caruso, Alessandro

2016-04-01

The past two decades have witnessed a huge progress in the development, implementation and testing of Earthquakes Early Warning Systems (EEWS) worldwide, as the result of a joint effort of the seismological and earthquake engineering communities to set up robust and efficient methodologies for the real-time seismic risk mitigation. This work presents an overview of the worldwide applications of the system PRESTo (PRobabilistic and Evolutionary early warning SysTem), which is the highly configurable and easily portable platform for Earthquake Early Warning developed by the RISSCLab group of the University of Naples Federico II. In particular, we first present the results of the real-time experimentation of PRESTo in Suthern Italy on the data streams of the Irpinia Seismic Network (ISNet), in Southern Italy. ISNet is a dense high-dynamic range, earthquake observing system, which operates in true real-time mode, thanks to a mixed data transmission system based on proprietary digital terrestrial links, standard ADSL and UMTS technologies. Using the seedlink protocol data are transferred to the network center unit, running the software platform PRESTo which is devoted to process the real-time data streaming, estimate source parameters and issue the alert. The software platform PRESTo uses a P-wave, network-based approach which has evolved and improved during the time since its first release. In its original version consisted in a series of modules, aimed at the event detection/picking, probabilistic real-time earthquake location and magnitude estimation, prediction of peak ground motion at distant sites through ground motion prediction equations for the area. In the recent years, PRESTo has been also implemented at the accelerometric and broad-band seismic networks in South Korea, Romania, North-East Italy, and Turkey and off-line tested in Iberian Peninsula, Israel, and Japan. Moreover, the feasibility of a PRESTo-based, EEWS at national scale in Italy, has been tested by evaluating its performance for the Italian Accelerometric Network. These testing experiments and the EEWS performance results will be summarized in the near-future perspective of building the next generation of early warning systems.

Experience from three years of local capacity development for tsunami early warning in Indonesia: challenges, lessons and the way ahead

NASA Astrophysics Data System (ADS)

Spahn, H.; Hoppe, M.; Vidiarina, H. D.; Usdianto, B.

2010-07-01

Five years after the 2004 tsunami, a lot has been achieved to make communities in Indonesia better prepared for tsunamis. This achievement is primarily linked to the development of the Indonesian Tsunami Early Warning System (InaTEWS). However, many challenges remain. This paper describes the experience with local capacity development for tsunami early warning (TEW) in Indonesia, based on the activities of a pilot project. TEW in Indonesia is still new to disaster management institutions and the public, as is the paradigm of Disaster Risk Reduction (DRR). The technology components of InaTEWS will soon be fully operational. The major challenge for the system is the establishment of clear institutional arrangements and capacities at national and local levels that support the development of public and institutional response capability at the local level. Due to a lack of information and national guidance, most local actors have a limited understanding of InaTEWS and DRR, and often show little political will and priority to engage in TEW. The often-limited capacity of local governments is contrasted by strong engagement of civil society organisations that opt for early warning based on natural warning signs rather than technology-based early warning. Bringing together the various actors, developing capacities in a multi-stakeholder cooperation for an effective warning system are key challenges for the end-to-end approach of InaTEWS. The development of local response capability needs to receive the same commitment as the development of the system's technology components. Public understanding of and trust in the system comes with knowledge and awareness on the part of the end users of the system and convincing performance on the part of the public service provider. Both sides need to be strengthened. This requires the integration of TEW into DRR, clear institutional arrangements, national guidance and intensive support for capacity development at local levels as well as dialogue between the various actors.

Early warning of orographically induced floods and landslides in Western Norway

NASA Astrophysics Data System (ADS)

Leine, Ann-Live; Wang, Thea; Boje, Søren

2017-04-01

In Western Norway, landslides and debris flows are commonly initiated by short-term orographic rainfall or intensity peaks during a prolonged rainfall event. In recent years, the flood warning service in Norway has evolved from being solely a flood forecasting service to also integrating landslides into its early warning systems. As both floods and landslides are closely related to the same hydrometeorological processes, particularly in small catchments, there is a natural synergy between monitoring flood and landslide risk. The Norwegian Flood and Landslide Hazard Forecasting and Warning Service issues regional landslide hazard warnings based on hydrological models, threshold values, observations and weather forecasts. Intense rainfall events and/or orographic precipitation that, under certain topographic conditions, significantly increase the risk of debris avalanches and debris floods are lately receiving more research focus from the Norwegian warning service. Orographic precipitation is a common feature in W-Norway, when moist and relatively mild air arrives from the Atlantic. Steep mountain slopes covered by glacial till makes the region prone to landslides, as well as flooding. The operational early warning system in Norway requires constant improvement, especially with the enhanced number of intense rainfall events that occur in a warming climate. Here, we examine different cases of intense rainfall events which have lead to landslides and debris flows, as well as increased runoff in fast responding small catchments. The main objective is to increase the understanding of the hydrometeorological conditions related to these events, in order to make priorities for the future development of the warning service.

Early warning system for aftershocks

USGS Publications Warehouse

Bakun, W.H.; Fischer, F.G.; Jensen, E.G.; VanSchaack, J.

1994-01-01

A prototype early warning system to provide San Francisco and Oakland, California a few tens-of-seconds warning of incoming strong ground shaking from already-occurred M ≧ 3.7 aftershocks of the magnitude 7.1 17 October 1989 Loma Prieta earthquake was operational on 28 October 1989. The prototype system consisted of four components: ground motion sensors in the epicentral area, a central receiver, a radio repeater, and radio receivers. One of the radio receivers was deployed at the California Department of Transportation (CALTRANS) headquarters at the damaged Cypress Street section of the I-880 freeway in Oakland, California on 28 October 1989 and provided about 20 sec of warning before shaking from the M 4.5 Loma Prieta aftershock that occurred on 2 November 1989 at 0550 UTC. In its first 6 months of operation, the system generated triggers for all 12 M > 3.7 aftershocks for which trigger documentation is preserved, did not trigger on any M ≦ 3.6 aftershocks, and produced one false trigger as a result of a now-corrected single point of failure design flaw. Because the prototype system demonstrated that potentially useful warnings of strong shaking from aftershocks are feasible, the USGS has completed a portable early warning system for aftershocks that can be deployed anywhere.

Research and application of a hybrid model based on dynamic fuzzy synthetic evaluation for establishing air quality forecasting and early warning system: A case study in China.

PubMed

Xu, Yunzhen; Du, Pei; Wang, Jianzhou

2017-04-01

As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants. Therefore, in this paper a novel robust early warning system was successfully developed, which consists of three modules: evaluation module, forecasting module and characteristics estimating module. In this system, a new dynamic fuzzy synthetic evaluation is proposed and applied to determine air quality levels and primary pollutants, which can be regarded as the research objectives; Moreover, to further mine and analyze the characteristics of air pollutants, four different distribution functions and interval forecasting method are also employed that can not only provide predictive range, confidence level and the other uncertain information of the pollutants future values, but also assist decision-makers in reducing and controlling the emissions of atmospheric pollutants. Case studies utilizing hourly PM 2.5 , PM 10 and SO 2 data collected from Tianjin and Shanghai in China are applied as illustrative examples to estimate the effectiveness and efficiency of the proposed system. Experimental results obviously indicated that the developed novel early warning system is much suitable for analyzing and monitoring air pollution, which can also add a novel viable option for decision-makers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Global early warning systems for natural hazards: systematic and people-centred.

PubMed

Basher, Reid

2006-08-15

To be effective, early warning systems for natural hazards need to have not only a sound scientific and technical basis, but also a strong focus on the people exposed to risk, and with a systems approach that incorporates all of the relevant factors in that risk, whether arising from the natural hazards or social vulnerabilities, and from short-term or long-term processes. Disasters are increasing in number and severity and international institutional frameworks to reduce disasters are being strengthened under United Nations oversight. Since the Indian Ocean tsunami of 26 December 2004, there has been a surge of interest in developing early warning systems to cater to the needs of all countries and all hazards.

Surveillance and early warning systems of infectious disease in China: From 2012 to 2014.

PubMed

Zhang, Honglong; Wang, Liping; Lai, Shengjie; Li, Zhongjie; Sun, Qiao; Zhang, Peng

2017-07-01

Appropriate surveillance and early warning of infectious diseases have very useful roles in disease control and prevention. In 2004, China established the National Notifiable Infectious Disease Surveillance System and the Public Health Emergency Event Surveillance System to report disease surveillance and events on the basis of data sources from the National Notifiable Infectious Disease Surveillance System, China Infectious Disease Automated-alert and Response System in this country. This study provided a descriptive summary and a data analysis, from 2012 to 2014, of these 3 key surveillance and early warning systems of infectious disease in China with the intent to provide suggestions for system improvement and perfection. Copyright © 2017 John Wiley & Sons, Ltd.

Evaluation of Passive Samplers as a Monitoring Tool for Early Warning of Dinophysis Toxins in Shellfish

PubMed Central

Pizarro, Gemita; Moroño, Ángeles; Paz, Beatriz; Franco, José M.; Pazos, Yolanda; Reguera, Beatriz

2013-01-01

From June 2006 to January 2007 passive samplers (solid phase adsorbing toxin tracking, SPATT) were tested as a monitoring tool with weekly monitoring of phytoplankton and toxin content (liquid chromatography–mass spectrometry, LC-MS) in picked cells of Dinophysis and plankton concentrates. Successive blooms of Dinophysis acuminata, D. acuta and D. caudata in 2006 caused a long mussel harvesting closure (4.5 months) in the Galician Rías (NW Spain) and a record (up to 9246 ng·g resin-week−1) accumulation of toxins in SPATT discs. Best fit of a toxin accumulation model was between toxin accumulation in SPATT and the product of cell densities by a constant value, for each species of Dinophysis, of toxin content (average) in picked cells. Detection of Dinophysis populations provided earlier warning of oncoming diarrhetic shellfish poisoning (DSP) outbreaks than the SPATT, which at times overestimated the expected toxin levels in shellfish because: (i) SPATT accumulated toxins did not include biotransformation and depuration loss terms and (ii) accumulation of toxins not available to mussels continued for weeks after Dinophysis cells were undetectable and mussels were toxin-free. SPATT may be a valuable environmental monitoring and research tool for toxin dynamics, in particular in areas with no aquaculture, but does not provide a practical gain for early warning of DSP outbreaks. PMID:24152559

Military Intervention to Stop Mass Atrocities

DTIC Science & Technology

2017-05-04

the circumstances where the United States should respond militarily. Early warning and prevention strategies are vital since these approaches allow...34genocide." As early as 1933, Lemkin addressed the issue of genocide in a paper he sent to a League of Nations conference in Madrid, Spain. He...2017, https://www.ushmm.org/confront- genocide/speakers-and-events/all-speakers-and-events/ early -warning-and-prevention/the-united-states- measures-to

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

A Distributed Architecture for Tsunami Early Warning and Collaborative Decision-support in Crises

NASA Astrophysics Data System (ADS)

Moßgraber, J.; Middleton, S.; Hammitzsch, M.; Poslad, S.

2012-04-01

The presentation will describe work on the system architecture that is being developed in the EU FP7 project TRIDEC on "Collaborative, Complex and Critical Decision-Support in Evolving Crises". The challenges for a Tsunami Early Warning System (TEWS) are manifold and the success of a system depends crucially on the system's architecture. A modern warning system following a system-of-systems approach has to integrate various components and sub-systems such as different information sources, services and simulation systems. Furthermore, it has to take into account the distributed and collaborative nature of warning systems. In order to create an architecture that supports the whole spectrum of a modern, distributed and collaborative warning system one must deal with multiple challenges. Obviously, one cannot expect to tackle these challenges adequately with a monolithic system or with a single technology. Therefore, a system architecture providing the blueprints to implement the system-of-systems approach has to combine multiple technologies and architectural styles. At the bottom layer it has to reliably integrate a large set of conventional sensors, such as seismic sensors and sensor networks, buoys and tide gauges, and also innovative and unconventional sensors, such as streams of messages from social media services. At the top layer it has to support collaboration on high-level decision processes and facilitates information sharing between organizations. In between, the system has to process all data and integrate information on a semantic level in a timely manner. This complex communication follows an event-driven mechanism allowing events to be published, detected and consumed by various applications within the architecture. Therefore, at the upper layer the event-driven architecture (EDA) aspects are combined with principles of service-oriented architectures (SOA) using standards for communication and data exchange. The most prominent challenges on this layer include providing a framework for information integration on a syntactic and semantic level, leveraging distributed processing resources for a scalable data processing platform, and automating data processing and decision support workflows.

Geoethical considerations in early warning of flooding and landslides: Case study from Norway

NASA Astrophysics Data System (ADS)

Devoli, Graziella; Kleivane Krøgli, Ingeborg; Dahl, Mads Peter; Colleuille, Hervé; Nykjær Boje, Søren; Sund, Monica

2015-04-01

The Norwegian Water Resources and Energy Directorate (NVE) runs the national early warning systems (EWS) for flooding and shallow landslides in Norway. The two EWSs have been operational since the late 1980s and 2013 respectively, and are based on weather forecasts, various hydro-meteorological prognosis and expert evaluation. Daily warning levels and related information to the public is prepared and presented through custom build internet platforms. In natural hazards sciences, the risk of a specific threat is defined as the product of hazard and consequence. In this context an EWS is intended to work as a mitigation measure in lowering the consequence and thus the risk of the threat. One of several factors determining the quality of such an EWS, is how warnings are communicated to the public. In contrary to what is common practice in some other countries, experts working with EWS in Norway cannot be held personally responsible for consequences of warnings being issued or not. However, the communication of warnings for flooding and landslides at NVE still implies many considerations of geoethical kind. Which are the consequences today for the forecasters when erroneous warning messages are sent because based on a poorly documented analysis? What is for example the most responsible way to describe uncertainties in warnings issued? What is the optimal compromise between avoiding false alarms and not sending out a specific warning? Is it responsible to rely on a "gut feeling"? Some authorities complain in receiving warning messages too often. Is it responsible to begin notifying these, only in cases of "high hazard level" and no longer in cases of "moderate hazard level"? Is it acceptable to issue general warnings for large geographical areas without being able to pinpoint the treat on local scale? What responsibility lies within the EWS in recommending evacuation or other practical measures to local authorities? By presenting how early warnings of flooding and landslides are communicated in Norway and discussing the questions above, we intend to add to the discussion on what is the ethical responsibility for scientists performing forecasting and communication of natural hazards.

Application of τc*Pd in earthquake early warning

NASA Astrophysics Data System (ADS)

Huang, Po-Lun; Lin, Ting-Li; Wu, Yih-Min

2015-03-01

Rapid assessment of damage potential and size of an earthquake at the station is highly demanded for onsite earthquake early warning. We study the application of τc*Pd for its estimation on the earthquake size using 123 events recorded by the borehole stations of KiK-net in Japan. The new type of earthquake size determined by τc*Pd is more related to the damage potential. We find that τc*Pd provides another parameter to measure the size of earthquake and the threshold to warn strong ground motion.

Early Warning Signs. A Solution-Finding Report

ERIC Educational Resources Information Center

Sullivan, Robert, Comp.

2017-01-01

This Solution-Finding Report provides information, requested by Tara Zuber with the Great Lakes Comprehensive Center (GLCC) at American Institutes for Research (AIR), for resources with evidence-based practices that look at the social and emotional causes that impact the lack of student learning and engagement, for GLCC's Early Warning Signs work.…

Research on Disaster Early Warning and Disaster Relief Integrated Service System Based on Block Data Theory

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, H.; Wang, C.; Tang, D.

2018-04-01

With the continuous development of social economy, the interaction between mankind and nature has become increasingly evident. Disastrous global catastrophes have occurred from time to time, causing huge losses to people's lives and property. All governments recognize the importance of the establishment of disaster early warning and release mechanisms, and it is also an urgent issue to improve the comprehensive service level of emergency response and disaster relief. However, disaster early warning and emergency relief information is usually generated by different departments, and the diverse data sources, difficult integration, and limited release speed have always been difficult issues to be solved. Block data is the aggregation of various distributed (point data) and segmentation (data) big data on a specific platform and make them happen continuous polymerization effect, block data theory is a good solution to cross-sectoral, cross-platform Disaster information data sharing and integration problems. This paper attempts to discuss the integrated service mechanism of disaster information aggregation and disaster relief based on block data theory and introduces a location-based integrated service system for disaster early warning and disaster relief.

The GNSS data processing component within the Indonesian tsunami early warning centre provided by GITEWS

NASA Astrophysics Data System (ADS)

Bartsch, M.; Merx, A.; Falck, C.; Ramatschi, M.

2010-05-01

Introduction Within the GITEWS (German Indonesian Tsunami Early Warning System) project a near real-time GNSS processing system has been developed, which analizes on- and offshore measured GNSS data. It is the first system of its kind that was integrated into an operational tsunami early warning system. (Indonesian Tsunami Early Warning Centre INATEWS, inaugurated at BMKG Jakarta on November, 11th 2008) Brief system description The GNSS data to be processed are received from sensors (GNSS antenna and receiver) installed on buoys, at tide gauges and as real-time reference stations (RTR stations), either stand-alone or co-located with seismic sensors. The GNSS data are transmitted to the warning centre in real-time as a stream (RTR stations) or file-based and are processed in a near real-time data processing chain. The fully automatized system uses the BERNESE GPS software as processing core. Kinematic coordinate timeseries with a resolution of 1 Hz (landbased stations) and 1/3 Hz (buoys) are estimated every five minutes. In case of a recently occured earthquake the processing interval decreases from five to two minutes. All stations are processed with the relative technique (baseline-technique) using GITEWS-stations and stations available via IGS as reference. The most suitable reference stations are choosen by querying a database where continiously monitored quality data of GNSS observations are stored. In case of an earthquake at least one reference station should be located on a different tectonic plate to ensure that relative movements can be detected. The primary source for satellite orbit information is the IGS IGU product. If this source is not available for any reason, the system switches automatically to other orbit sources like CODE products or broadcast ephemeris data. For sensors on land the kinematic coordinates are used to detect deviations from their normal, mean coordinates. The deviations or so called displacements are indicators for land mass movements which can occur, e.g., due to strong earthquakes. The ground motion information is a valuable source for a fast understanding of an earthquake's mechanism and consequences with possible relevance for a potentially following tsunami. Regarding kinematic coordinates of a buoy only the vertical component is of interest as it corresponds to the instant sea level. The kinematic coordinates are delivered to an oceanographic post-processing unit which applies dipping-, tilting- and tidal-corrections to the data. Deviations to the mean sea level are an indicator for a possibly passing tsunami wave. By this means the GNSS system supports the decision finding process whether a tsunami has been released or not. A graphical user interface (GUI) was developed which monitors the whole processing chain from data transmission and GNSS data processing to the displaying of the kinematic coordinate time series. It supports both, a quick view for all staff members at the warning centre (24h/7d shifts) and deeper analysis by GNSS experts. The GNSS GUI system is web-based and allows all views to be displayed on different screens at the same time, even at remote locations. This is part of the concept, as it can support the dialogue between warning centre staff on duty or on standby and sensor station maintenance staff. Acknowledgements The GITEWS project (German Indonesian Tsunami Early Warning System) is carried out by a large group of scientists and engineers from (GFZ) German Research Centre for Geosciences and its partners from the German Aerospace Centre (DLR), the Alfred Wegener Institute for Polar and Marine Research (AWI), the GKSS Research Centre, the Konsortium Deutsche Meeresforschung (KDM), the Leibniz Institute for Marine Sciences (IFM-GEOMAR), the United Nations University (UNU), the Federal Institute for Geosciences and Natural Resources (BGR), the German Agency for Technical Cooperation (GTZ) and other international partners. Most relevant partners in Indonesia with respect to the GNSS component of GITEWS are the National Coordinating Agency for Surveys and Mapping (BAKOSURTANAL), the National Metereology and Geophysics Agency (BMG) and the National Agency for the Assessment and Application of Technology (BPPT). Funding is provided by the German Federal Ministry for Education and Research (BMBF), Grant 03TSU01.

Detection of warning surfaces in pedestrian environments: the importance for blind people of kerbs, depth, and structure of tactile surfaces.

PubMed

Ståhl, Agneta; Newman, Emma; Dahlin-Ivanoff, Synneve; Almén, Mai; Iwarsson, Sussane

2010-01-01

The overall purpose was to study whether and how persons with blindness detect warning surfaces with a long white cane in a real pedestrian environment after following a natural guidance surface to the warning surfaces. Of particular interest was the importance of kerb, depth, and structure of the warning surfaces. A concurrently mixed methods approach, with a combination of observation using a structured form together with 'think aloud' and a structured interview, was used. It was done with well-defined samples and study sites in an inter-disciplinary research context. The results show that the most important design characteristic for detection of the warning surfaces with a white cane is the structure of the surface, while the depth of the surface and availability of a kerb do not have any impact on the detection. A precondition was that there is a distinct natural guidance surface leading up to the warning surface. The probability among pedestrians with blindness to detect a tactile surface is not higher if the design solution has a kerb. This study also confirms the complexity of being a blind pedestrian in the traffic environment. The results can be used for evidence-based physical planning. The study also has implications for development of more efficient vision rehabilitation.

Forecasting weed distributions using climate data: a GIS early warning tool

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Barnett, David T.; Stohlgren, Thomas J.; Kartesz, John T.

2010-01-01

The number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in­-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest, and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimaric envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that county's list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.

Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

PubMed

Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

2013-11-30

Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Relation between stability and resilience determines the performance of early warning signals under different environmental drivers.

PubMed

Dai, Lei; Korolev, Kirill S; Gore, Jeff

2015-08-11

Shifting patterns of temporal fluctuations have been found to signal critical transitions in a variety of systems, from ecological communities to human physiology. However, failure of these early warning signals in some systems calls for a better understanding of their limitations. In particular, little is known about the generality of early warning signals in different deteriorating environments. In this study, we characterized how multiple environmental drivers influence the dynamics of laboratory yeast populations, which was previously shown to display alternative stable states [Dai et al., Science, 2012]. We observed that both the coefficient of variation and autocorrelation increased before population collapse in two slowly deteriorating environments, one with a rising death rate and the other one with decreasing nutrient availability. We compared the performance of early warning signals across multiple environments as "indicators for loss of resilience." We find that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability (recovery rate) and resilience (size of the basin of attraction). Furthermore, we demonstrate that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down in this system when multiple environmental drivers are changed simultaneously. Our results suggest that the stability-resilience relation needs to be better understood for the application of early warning signals in different scenarios.

Relation between stability and resilience determines the performance of early warning signals under different environmental drivers

PubMed Central

Dai, Lei; Korolev, Kirill S.; Gore, Jeff

2015-01-01

Shifting patterns of temporal fluctuations have been found to signal critical transitions in a variety of systems, from ecological communities to human physiology. However, failure of these early warning signals in some systems calls for a better understanding of their limitations. In particular, little is known about the generality of early warning signals in different deteriorating environments. In this study, we characterized how multiple environmental drivers influence the dynamics of laboratory yeast populations, which was previously shown to display alternative stable states [Dai et al., Science, 2012]. We observed that both the coefficient of variation and autocorrelation increased before population collapse in two slowly deteriorating environments, one with a rising death rate and the other one with decreasing nutrient availability. We compared the performance of early warning signals across multiple environments as “indicators for loss of resilience.” We find that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability (recovery rate) and resilience (size of the basin of attraction). Furthermore, we demonstrate that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down in this system when multiple environmental drivers are changed simultaneously. Our results suggest that the stability–resilience relation needs to be better understood for the application of early warning signals in different scenarios. PMID:26216946

[Analysis and experimental verification of sensitivity and SNR of laser warning receiver].

PubMed

Zhang, Ji-Long; Wang, Ming; Tian, Er-Ming; Li, Xiao; Wang, Zhi-Bin; Zhang, Yue

2009-01-01

In order to countermeasure increasingly serious threat from hostile laser in modern war, it is urgent to do research on laser warning technology and system, and the sensitivity and signal to noise ratio (SNR) are two important performance parameters in laser warning system. In the present paper, based on the signal statistical detection theory, a method for calculation of the sensitivity and SNR in coherent detection laser warning receiver (LWR) has been proposed. Firstly, the probabilities of the laser signal and receiver noise were analyzed. Secondly, based on the threshold detection theory and Neyman-Pearson criteria, the signal current equation was established by introducing detection probability factor and false alarm rate factor, then, the mathematical expressions of sensitivity and SNR were deduced. Finally, by using method, the sensitivity and SNR of the sinusoidal grating laser warning receiver developed by our group were analyzed, and the theoretic calculation and experimental results indicate that the SNR analysis method is feasible, and can be used in performance analysis of LWR.

A fundamental conflict of care: Nurses' accounts of balancing patients' sleep with taking vital sign observations at night.

PubMed

Hope, Joanna; Recio-Saucedo, Alejandra; Fogg, Carole; Griffiths, Peter; Smith, Gary B; Westwood, Greta; Schmidt, Paul E

2017-12-21

To explore why adherence to vital sign observations scheduled by an early warning score protocol reduces at night. Regular vital sign observations can reduce avoidable deterioration in hospital. early warning score protocols set the frequency of these observations by the severity of a patient's condition. Vital sign observations are taken less frequently at night, even with an early warning score in place, but no literature has explored why. A qualitative interpretative design informed this study. Seventeen semi-structured interviews with nursing staff working on wards with varying levels of adherence to scheduled vital sign observations. A thematic analysis approach was used. At night, nursing teams found it difficult to balance the competing care goals of supporting sleep with taking vital sign observations. The night-time frequency of these observations was determined by clinical judgement, ward-level expectations of observation timing and the risk of disturbing other patients. Patients with COPD or dementia could be under-monitored, while patients nearing the end of life could be over-monitored. In this study, we found an early warning score algorithm focused on deterioration prevention did not account for long-term management or palliative care trajectories. Nurses were therefore less inclined to wake such patients to take vital sign observations at night. However, the perception of widespread exceptions and lack of evidence regarding optimum frequency risks delegitimising the early warning score approach. This may pose a risk to patient safety, particularly patients with dementia or chronic conditions. Nurses should document exceptions and discuss these with the wider team. Hospitals should monitor why vital sign observations are missed at night, identify which groups are under-monitored and provide guidance on prioritising competing expectations. early warning score protocols should take account of different care trajectories. © 2017 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William W.; Gasser, Gerald; Norman, Steve

2013-01-01

U.S. forests occupy approx.1/3 of total land area (approx. 304 million ha). Since 2000, a growing number of regionally evident forest disturbances have occurred due to abiotic and biotic agents. Regional forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest disturbance monitoring products are needed to aid forest health management work. Near Real Time (NRT) twice daily MODIS NDVI data provide a means to monitor U.S. regional forest disturbances every 8 days. Since 2010, these NRT forest change products have been produced and posted on the US Forest Service ForWarn Early Warning System for Forest Threats.

[Results of applying a paediatric early warning score system as a healthcare quality improvement plan].

PubMed

Rivero-Martín, M J; Prieto-Martínez, S; García-Solano, M; Montilla-Pérez, M; Tena-Martín, E; Ballesteros-García, M M

2016-06-01

The aims of this study were to introduce a paediatric early warning score (PEWS) into our daily clinical practice, as well as to evaluate its ability to detect clinical deterioration in children admitted, and to train nursing staff to communicate the information and response effectively. An analysis was performed on the implementation of PEWS in the electronic health records of children (0-15 years) in our paediatric ward from February 2014 to September 2014. The maximum score was 6. Nursing staff reviewed scores >2, and if >3 medical and nursing staff reviewed it. Monitoring indicators: % of admissions with scoring; % of complete data capture; % of scores >3; % of scores >3 reviewed by medical staff, % of changes in treatment due to the warning system, and number of patients who needed Paediatric Intensive Care Unit (PICU) admission, or died without an increased warning score. The data were collected from all patients (931) admitted. The scale was measured 7,917 times, with 78.8% of them with complete data capture. Very few (1.9%) showed scores >3, and 14% of them with changes in clinical management (intensifying treatment or new diagnostic tests). One patient (scored 2) required PICU admission. There were no deaths. Parents or nursing staff concern was registered in 80% of cases. PEWS are useful to provide a standardised assessment of clinical status in the inpatient setting, using a unique scale and implementing data capture. Because of the lack of severe complications requiring PICU admission and deaths, we will have to use other data to evaluate these scales. Copyright © 2016 SECA. Published by Elsevier Espana. All rights reserved.

Early warning signals for critical transitions in a thermoacoustic system

PubMed Central

Gopalakrishnan, E. A.; Sharma, Yogita; John, Tony; Dutta, Partha Sharathi; Sujith, R. I.

2016-01-01

Dynamical systems can undergo critical transitions where the system suddenly shifts from one stable state to another at a critical threshold called the tipping point. The decrease in recovery rate to equilibrium (critical slowing down) as the system approaches the tipping point can be used to identify the proximity to a critical transition. Several measures have been adopted to provide early indications of critical transitions that happen in a variety of complex systems. In this study, we use early warning indicators to predict subcritical Hopf bifurcation occurring in a thermoacoustic system by analyzing the observables from experiments and from a theoretical model. We find that the early warning measures perform as robust indicators in the presence and absence of external noise. Thus, we illustrate the applicability of these indicators in an engineering system depicting critical transitions. PMID:27767065

An in-situ infection detection sensor coating for urinary catheters

PubMed Central

Milo, Scarlet; Thet, Naing Tun; Liu, Dan; Nzakizwanayo, Jonathan; Jones, Brian V.; Jenkins, A. Toby A.

2016-01-01

We describe a novel infection-responsive coating for urinary catheters that provides a clear visual early warning of Proteus mirabilis infection and subsequent blockage. The crystalline biofilms of P. mirabilis can cause serious complications for patients undergoing long-term bladder catheterisation. Healthy urine is around pH 6, bacterial urease increases urine pH leading to the precipitation of calcium and magnesium deposits from the urine, resulting in dense crystalline biofilms on the catheter surface that blocks urine flow. The coating is a dual layered system in which the lower poly(vinyl alcohol) layer contains the self-quenching dye carboxyfluorescein. This is capped by an upper layer of the pH responsive polymer poly(methyl methacrylate-co-methacrylic acid) (Eudragit S100®). Elevation of urinary pH (>pH 7) dissolves the Eudragit layer, releasing the dye to provide a clear visual warning of impending blockage. Evaluation of prototype coatings using a clinically relevant in vitro bladder model system demonstrated that coatings provide up to 12 h advanced warning of blockage, and are stable both in the absence of infection, and in the presence of species that do not cause catheter blockage. At the present time, there are no effective methods to control these infections or provide warning of impending catheter blockage. PMID:26945183

Development and Experimental Application of International Affairs Indicators. Volume B. Supportive Research

DTIC Science & Technology

1974-06-01

i INDICATORS Approaches to Early Warning The Quantitative Indicators Approach: A ... 5 Summary Indicators and Early Warning...Indicators for Early ^ Wa rning 3. Quantitative Signs of Unusual or Ominous Activity 9 13 4. Simulated Cables 25 5 . TEXSCAN...Behavior) for Czechoslovakia 1 mmmmm mmm LIST OF FIGURES vi Pa£« 1. 2. 3. 4. 5 . 6. 7. 8. 9. 10. U. 12. 13. 14. 15. 16. 17. 18

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities

PubMed Central

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the “S&P 500 1987” bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs. PMID:27806093

Vulnerabilities of macrophytes distribution due to climate change

NASA Astrophysics Data System (ADS)

Hossain, Kaizar; Yadav, Sarita; Quaik, Shlrene; Pant, Gaurav; Maruthi, A. Y.; Ismail, Norli

2017-08-01

The rise in the earth's surface and water temperature is part of the effect of climatic change that has been observed for the last decade. The rates of climate change are unprecedented, and biological responses to these changes have also been prominent in all levels of species, communities and ecosystems. Aquatic-terrestrial ecotones are vulnerable to climate change, and degradation of the emergent aquatic macrophyte zone would have contributed severe ecological consequences for freshwater, wetland and terrestrial ecosystems. Most researches on climate change effects on biodiversity are contemplating on the terrestrial realm, and considerable changes in terrestrial biodiversity and species' distributions have been detected in response to climate change. This is unfortunate, given the importance of aquatic systems for providing ecosystem goods and services. Thus, if researchers were able to identify early-warning indicators of anthropogenic environmental changes on aquatic species, communities and ecosystems, it would certainly help to manage and conserve these systems in a sustainable way. One of such early-warning indicators concerns the expansion of emergent macrophytes in aquatic-terrestrial ecotones. Hence, this review highlights the impact of climatic changes towards aquatic macrophytes and their possible environmental implications.

Experiences from site-specific landslide early warning systems

NASA Astrophysics Data System (ADS)

Michoud, C.; Bazin, S.; Blikra, L. H.; Derron, M.-H.; Jaboyedoff, M.

2013-10-01

Landslide early warning systems (EWSs) have to be implemented in areas with large risk for populations or infrastructures when classical structural remediation measures cannot be set up. This paper aims to gather experiences of existing landslide EWSs, with a special focus on practical requirements (e.g., alarm threshold values have to take into account the smallest detectable signal levels of deployed sensors before being established) and specific issues when dealing with system implementations. Within the framework of the SafeLand European project, a questionnaire was sent to about one-hundred institutions in charge of landslide management. Finally, we interpreted answers from experts belonging to 14 operational units related to 23 monitored landslides. Although no standard requirements exist for designing and operating EWSs, this review highlights some key elements, such as the importance of pre-investigation work, the redundancy and robustness of monitoring systems, the establishment of different scenarios adapted to gradual increasing of alert levels, and the necessity of confidence and trust between local populations and scientists. Moreover, it also confirms the need to improve our capabilities for failure forecasting, monitoring techniques and integration of water processes into landslide conceptual models.

Adolescents perceived effectiveness of the proposed European graphic tobacco warning labels.

PubMed

Vardavas, Constantine I; Connolly, Gregory; Karamanolis, Kostas; Kafatos, Anthony

2009-04-01

Graphical tobacco product labelling is a prominent source of health information and has an important position among tobacco control initiatives. However, little is known about its effectiveness among adolescents. With this above in mind, we aimed to research into how adolescents perceive the proposed EU graphic tobacco product warning labels as an effective means of preventing smoking initiation in comparison to the current EU text-only warning labels. Five hundred seventy four adolescents (13-18, 54% male) from Greece were privately interviewed, with the use of a digital questionnaire and randomly shown seven existing EU text-only and proposed EU graphic warning labels. Non-smoking respondents were asked to compare and rate the warnings effectiveness in regard to preventing them from smoking on a 1-5 Likert type scale. Irrespective of the warning category shown, on all occasions, non-smoking adolescents rated the suggested EU graphic labels as more effective in preventing them from smoking in comparison to the existing EU text-only warnings. Controlling for gender, age, current smoking status and number of cigarettes smoked per month, younger adolescents were found to opt for graphic warnings more often, and also perceive graphic warning labels as a more effective means of preventing them from smoking, in comparison to their elder peers (P < 0.001). The proposed EU graphic warning labels may play an important role in preventing of smoking initiation during the crucial years of early adolescence when smoking experimentation and early addiction usually take place.

Firefly Algorithm in detection of TEC seismo-ionospheric anomalies

NASA Astrophysics Data System (ADS)

Akhoondzadeh, Mehdi

2015-07-01

Anomaly detection in time series of different earthquake precursors is an essential introduction to create an early warning system with an allowable uncertainty. Since these time series are more often non linear, complex and massive, therefore the applied predictor method should be able to detect the discord patterns from a large data in a short time. This study acknowledges Firefly Algorithm (FA) as a simple and robust predictor to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of the some powerful earthquakes including Chile (27 February 2010), Varzeghan (11 August 2012) and Saravan (16 April 2013). Outstanding anomalies were observed 7 and 5 days before the Chile and Varzeghan earthquakes, respectively and also 3 and 8 days prior to the Saravan earthquake.

Development and Use of Early Warning Systems. SLDS Spotlight

ERIC Educational Resources Information Center

Curtin, Jenny; Hurwitch, Bill; Olson, Tom

2012-01-01

An early warning system is a data-based tool that helps predict which students are on the right path towards eventual graduation or other grade-appropriate goals. Through such systems, stakeholders at the school and district levels can view data from a wide range of perspectives and gain a deeper understanding of student data. This "Statewide…

Early Warning Indicator System: Supporting K-12 Educators in the Identification, Support, and Monitoring of At-Risk Students

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2016

2016-01-01

A rise in data availability gives educators the opportunity to tailor instructional practices and interventions to student needs and invest resources in areas where students require the most support. Massachusetts developed the Early Warning Indicator System (EWIS), which synthesizes the wealth of student data available in the state, including…

Regional drought early warning, impacts, and assessment for water and agriculture in the lower Rio Grande basin, 2016-2017

USDA-ARS?s Scientific Manuscript database

USDA’s Southern Plains Climate Hub (SPCH) and the University of Oklahoma’s Southern Climate Impacts Planning Program (SCIPP) contributed to a broad, multi-partnered effort to provide drought early warning information to water and agriculture management interests in the middle and lower Rio Grande ba...

A Practitioner's Guide to Implementing Early Warning Systems. REL 2015-056

ERIC Educational Resources Information Center

Frazelle, Sarah; Nagel, Aisling

2015-01-01

To stem the tide of students dropping out, many schools and districts are turning to early warning systems (EWS) that signal whether a student is at risk of not graduating from high school. While some research exists about establishing these systems, there is little information about the actual implementation strategies that are being used across…

An Analysis of the 1992 New Jersey Grade 8 Early Warning Test.

ERIC Educational Resources Information Center

Tambini, Robert F.

The quality and the effectiveness of the 1992 New Jersey Grade 8 Early Warning Test (NJEWT) are assessed. Standardized tests possess clear advantages for educators, especially in the case of administration and scoring, but there are clear disadvantages as well, including the possibility of bias. Four criteria are applied to the NJEWT: adequacy,…

Overview and highlights of Early Warning and Crop Condition Assessment project

NASA Technical Reports Server (NTRS)

Boatwright, G. O.; Whitehead, V. S.

1985-01-01

Work of the Early Warning and Crop Condition Assessment (EW/CCA) project, one of eight projects in the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS), is reviewed. Its mission, to develop and test remote sensing techniques that enhance operational methodologies for crop condition assessment, was in response to initiatives issued by the Secretary of Agriculture. Meteorologically driven crop stress indicator models have been developed or modified for wheat, maize, grain sorghum, and soybeans. These models provide early warning alerts of potential or actual crop stresses due to water deficits, adverse temperatures, and water excess that could delay planting or harvesting operations. Recommendations are given for future research involving vegetative index numbers and the NOAA and Landsat satellites.

Use of a SQUID array to detect T-cells with magnetic nanoparticles in determining transplant rejection

NASA Astrophysics Data System (ADS)

Flynn, Edward R.; Bryant, H. C.; Bergemann, Christian; Larson, Richard S.; Lovato, Debbie; Sergatskov, Dmitri A.

2007-04-01

Acute rejection in organ transplant is signaled by the proliferation of T-cells that target and kill the donor cells requiring painful biopsies to detect rejection onset. An alternative non-invasive technique is proposed using a multi-channel superconducting quantum interference device (SQUID) magnetometer to detect T-cell lymphocytes in the transplanted organ labeled with magnetic nanoparticles conjugated to antibodies specifically attached to lymphocytic ligand receptors. After a magnetic field pulse, the T-cells produce a decaying magnetic signal with a characteristic time of the order of a second. The extreme sensitivity of this technique, 10 5 cells, can provide early warning of impending transplant rejection and monitor immune-suppressive chemotherapy.

Sensor data monitoring and decision level fusion scheme for early fire detection

NASA Astrophysics Data System (ADS)

Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2017-05-01

The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.

An analysis of the early-warning system in emerging markets for reducing the financial crisis

NASA Astrophysics Data System (ADS)

Shen, Xiangguang; Song, Xiaozhong

2009-07-01

The large number of financial crises in emerging markets over the past ten years has left many observers, both from academia and financial institutions, puzzled by an apparent lack of homogenous causal relations between endogenous economic variables and the bursting of large financial shocks. The frequency of financial crises in the last 20 years can be attributed to the lack of a comprehensive theory of financial regulation to guide policy makers. Existing theories fail to define the range of regulatory models, the causes of regulatory failure, and how to measure and prevent it. Faulty design of regulatory models, and the lack of ongoing performance monitoring incorporating early warning systems, is disrupting economic and social development. The main aim of this article is to propose an early warning system (EWS) which purposes issuing warning signal against the possible financial crisis in the emerging market, and makes the emerging market survived the first wave of the crisis be able to continue their operation in the following years.

Ladar-based IED detection

NASA Astrophysics Data System (ADS)

Engström, Philip; Larsson, Hâkan; Letalick, Dietmar

2014-05-01

An improvised explosive device (IED) is a bomb constructed and deployed in a non-standard manor. Improvised means that the bomb maker took whatever he could get his hands on, making it very hard to predict and detect. Nevertheless, the matters in which the IED's are deployed and used, for example as roadside bombs, follow certain patterns. One possible approach for early warning is to record the surroundings when it is safe and use this as reference data for change detection. In this paper a LADAR-based system for IED detection is presented. The idea is to measure the area in front of the vehicle when driving and comparing this to the previously recorded reference data. By detecting new, missing or changed objects the system can make the driver aware of probable threats.

Health management system for rocket engines

NASA Technical Reports Server (NTRS)

Nemeth, Edward

1990-01-01

The functional framework of a failure detection algorithm for the Space Shuttle Main Engine (SSME) is developed. The basic algorithm is based only on existing SSME measurements. Supplemental measurements, expected to enhance failure detection effectiveness, are identified. To support the algorithm development, a figure of merit is defined to estimate the likelihood of SSME criticality 1 failure modes and the failure modes are ranked in order of likelihood of occurrence. Nine classes of failure detection strategies are evaluated and promising features are extracted as the basis for the failure detection algorithm. The failure detection algorithm provides early warning capabilities for a wide variety of SSME failure modes. Preliminary algorithm evaluation, using data from three SSME failures representing three different failure types, demonstrated indications of imminent catastrophic failure well in advance of redline cutoff in all three cases.

Electrical Distribution System (EDS) and Caution and Warning System (CWS)

NASA Technical Reports Server (NTRS)

Mcclung, T.

1975-01-01

An astronaut caution and warning system is described which monitors various life support system parameters and detects out-of-range parameter conditions. The warning system generates a warning tone and displays the malfunction condition to the astronaut along with the proper corrective procedures required.

76 FR 35327 - Airworthiness Directives; The Boeing Company Model 737-600, -700, -700C, -800, -900, and -900ER...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-17

... stabilizer takeoff warning switches, and corrective actions if necessary. This AD was prompted by reports that the warning horn did not sound during the takeoff warning system test of the S132 ``nose up stab takeoff warning switch.'' We are issuing this AD to detect and correct a takeoff warning system switch...

75 FR 55691 - Airworthiness Directives; The Boeing Company Model 737-600, -700, -700C, -800, -900, and -900ER...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-14

... takeoff warning switches, and corrective actions if necessary. This proposed AD results from reports that the warning horn did not sound during the takeoff warning system test of the S132 ``nose up stab takeoff warning switch.'' We are proposing this AD to detect and correct a takeoff warning system switch...

Size Matters a Lot: Drought-Affected Italian Oaks Are Smaller and Show Lower Growth Prior to Tree Death.

PubMed

Colangelo, Michele; Camarero, Jesús J; Borghetti, Marco; Gazol, Antonio; Gentilesca, Tiziana; Ripullone, Francesco

2017-01-01

Hydraulic theory suggests that tall trees are at greater risk of drought-triggered death caused by hydraulic failure than small trees. In addition the drop in growth, observed in several tree species prior to death, is often interpreted as an early-warning signal of impending death. We test these hypotheses by comparing size, growth, and wood-anatomy patterns of living and now-dead trees in two Italian oak forests showing recent mortality episodes. The mortality probability of trees is modeled as a function of recent growth and tree size. Drift-diffusion-jump (DDJ) metrics are used to detect early-warning signals. We found that the tallest trees of the anisohydric Italian oak better survived drought contrary to what was predicted by the theory. Dead trees were characterized by a lower height and radial-growth trend than living trees in both study sites. The growth reduction of now-dead trees started about 10 years prior to their death and after two severe spring droughts during the early 2000s. This critical transition in growth was detected by DDJ metrics in the most affected site. Dead trees were also more sensitive to drought stress in this site indicating different susceptibility to water shortage between trees. Dead trees did not form earlywood vessels with smaller lumen diameter than surviving trees but tended to form wider latewood vessels with a higher percentage of vessel area. Since living and dead trees showed similar competition we did not expect that moderate thinning and a reduction in tree density would increase the short-term survival probability of trees.

Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example.

PubMed

Negahbani, Ehsan; Steyn-Ross, D Alistair; Steyn-Ross, Moira L; Aguirre, Luis A

2016-01-01

Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent study has reported silent early warning signals obtained from P and A populations prior to saddle-node (SN) bifurcation, and thus concluded that early warning signals are not universal. By performing a full eigenvalue analysis of the same system we demonstrate that while J and P populations undergo SN bifurcation, A does not jump to a new state, so it is not expected to carry early warning signs. In contrast with the previous study, we capture a significant increase in the noise-induced fluctuations in the P population, but only on close approach to the bifurcation point; it is not clear why the P variance initially shows a decaying trend. Here we resolve this puzzle using observability measures from control theory. By computing the observability coefficient for the system from the recordings of each population considered one at a time, we are able to quantify their ability to describe changing internal dynamics. We demonstrate that precursor fluctuations are best observed using only the J variable, and also P variable if close to transition. Using observability analysis we are able to describe why a poorly observable variable (P) has poor forecasting capabilities although a full eigenvalue analysis shows that this variable undergoes a bifurcation. We conclude that observability analysis provides complementary information to identify the variables carrying early-warning signs about impending state transition.

A triangular climate-based decision model to forecast crop anomalies in Kenya

NASA Astrophysics Data System (ADS)

Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

2017-12-01

By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

Outbreak detection and evaluation of a school-based influenza-like-illness syndromic surveillance in Tianjin, China.

PubMed

Xu, Wenti; Chen, Tianmu; Dong, Xiaochun; Kong, Mei; Lv, Xiuzhi; Li, Lin

2017-01-01

School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median Runc of 4.62. The interventions in each outbreak had high effectiveness and all Rcon were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.

A Risk Assessment System with Automatic Extraction of Event Types

NASA Astrophysics Data System (ADS)

Capet, Philippe; Delavallade, Thomas; Nakamura, Takuya; Sandor, Agnes; Tarsitano, Cedric; Voyatzi, Stavroula

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Early Warning and Outbreak Detection Using Social Networking Websites: The Potential of Twitter

NASA Astrophysics Data System (ADS)

de Quincey, Ed; Kostkova, Patty

Epidemic Intelligence is being used to gather information about potential diseases outbreaks from both formal and increasingly informal sources. A potential addition to these informal sources are social networking sites such as Facebook and Twitter. In this paper we describe a method for extracting messages, called "tweets" from the Twitter website and the results of a pilot study which collected over 135,000 tweets in a week during the current Swine Flu pandemic.

Technologies and Techniques for Early Warning Systems to Monitor and Evaluate Drinking Water Quality: A State-of-the-Art Review

DTIC Science & Technology

2005-08-25

tests currently available are the same as BTA with the inclusion of Vibrio cholerae O1. The detection limits of bacteria are 10 cfu/mL and for...spp., Burkholderia spp., Campylobacter spp., Clostridium perfringens, E. coli O157:H7, Francisella tularensis, Salmonella typhi, Shigella spp., Vibrio ... cholerae O1, Yersinia pestis, Y. enterocolitica Viruses Caliciviruses, Enteroviruses, Hepatitis A/E, Variola, Venezuelan equine encephalitis virus

Big Data and the Global Public Health Intelligence Network (GPHIN)

PubMed Central

Dion, M; AbdelMalik, P; Mawudeku, A

2015-01-01

Background Globalization and the potential for rapid spread of emerging infectious diseases have heightened the need for ongoing surveillance and early detection. The Global Public Health Intelligence Network (GPHIN) was established to increase situational awareness and capacity for the early detection of emerging public health events. Objective To describe how the GPHIN has used Big Data as an effective early detection technique for infectious disease outbreaks worldwide and to identify potential future directions for the GPHIN. Findings Every day the GPHIN analyzes over more than 20,000 online news reports (over 30,000 sources) in nine languages worldwide. A web-based program aggregates data based on an algorithm that provides potential signals of emerging public health events which are then reviewed by a multilingual, multidisciplinary team. An alert is sent out if a potential risk is identified. This process proved useful during the Severe Acute Respiratory Syndrome (SARS) outbreak and was adopted shortly after by a number of countries to meet new International Health Regulations that require each country to have the capacity for early detection and reporting. The GPHIN identified the early SARS outbreak in China, was credited with the first alert on MERS-CoV and has played a significant role in the monitoring of the Ebola outbreak in West Africa. Future developments are being considered to advance the GPHIN’s capacity in light of other Big Data sources such as social media and its analytical capacity in terms of algorithm development. Conclusion The GPHIN’s early adoption of Big Data has increased global capacity to detect international infectious disease outbreaks and other public health events. Integration of additional Big Data sources and advances in analytical capacity could further strengthen the GPHIN’s capability for timely detection and early warning. PMID:29769954

Molecular probes and microarrays for the detection of toxic algae in the genera Dinophysis and Phalacroma (Dinophyta).

PubMed

Edvardsen, Bente; Dittami, Simon M; Groben, René; Brubak, Sissel; Escalera, Laura; Rodríguez, Francisco; Reguera, Beatriz; Chen, Jixin; Medlin, Linda K

2013-10-01

Dinophysis and Phalacroma species containing diarrheic shellfish toxins and pectenotoxins occur in coastal temperate waters all year round and prevent the harvesting of mussels during several months each year in regions in Europe, Chile, Japan, and New Zealand. Toxicity varies among morphologically similar species, and a precise identification is needed for early warning systems. Molecular techniques using ribosomal DNA sequences offer a means to identify and detect precisely the potentially toxic species. We designed molecular probes targeting the 18S rDNA at the family and genus levels for Dinophysis and Phalacroma and at the species level for Dinophysis acuminata, Dinophysis acuta, and Dinophysis norvegica, the most commonly occurring, potentially toxic species of these genera in Western European waters. Dot blot hybridizations with polymerase chain reaction (PCR)-amplified rDNA from 17 microalgae were used to demonstrate probe specificity. The probes were modified along with other published fluorescence in situ hybridization and PCR probes and tested for a microarray platform within the MIDTAL project ( http://www.midtal.com ). The microarray was applied to field samples from Norway and Spain and compared to microscopic cell counts. These probes may be useful for early warning systems and monitoring and can also be used in population dynamic studies to distinguish species and life cycle stages, such as cysts, and their distribution in time and space.

An Architecture for Automated Fire Detection Early Warning System Based on Geoprocessing Service Composition

NASA Astrophysics Data System (ADS)

Samadzadegan, F.; Saber, M.; Zahmatkesh, H.; Joze Ghazi Khanlou, H.

2013-09-01

Rapidly discovering, sharing, integrating and applying geospatial information are key issues in the domain of emergency response and disaster management. Due to the distributed nature of data and processing resources in disaster management, utilizing a Service Oriented Architecture (SOA) to take advantages of workflow of services provides an efficient, flexible and reliable implementations to encounter different hazardous situation. The implementation specification of the Web Processing Service (WPS) has guided geospatial data processing in a Service Oriented Architecture (SOA) platform to become a widely accepted solution for processing remotely sensed data on the web. This paper presents an architecture design based on OGC web services for automated workflow for acquisition, processing remotely sensed data, detecting fire and sending notifications to the authorities. A basic architecture and its building blocks for an automated fire detection early warning system are represented using web-based processing of remote sensing imageries utilizing MODIS data. A composition of WPS processes is proposed as a WPS service to extract fire events from MODIS data. Subsequently, the paper highlights the role of WPS as a middleware interface in the domain of geospatial web service technology that can be used to invoke a large variety of geoprocessing operations and chaining of other web services as an engine of composition. The applicability of proposed architecture by a real world fire event detection and notification use case is evaluated. A GeoPortal client with open-source software was developed to manage data, metadata, processes, and authorities. Investigating feasibility and benefits of proposed framework shows that this framework can be used for wide area of geospatial applications specially disaster management and environmental monitoring.