scholarly journals Maximizing the Resilience of Healthcare Workers in Multi-hazard Events: Lessons from the 2014–2015 Ebola Response in Africa

2019 ◽  
Vol 184 (Supplement_1) ◽  
pp. 114-120 ◽  
Author(s):  
Merritt Schreiber ◽  
David S Cates ◽  
Stephen Formanski ◽  
Michael King
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Action Plan ◽  
Full Range ◽  
The Philippines ◽  
System Component ◽  
Risk And Resilience ◽  
Post Traumatic Stress ◽  
Triage System ◽  
Pilot Work

Abstract There is increasing knowledge that health care workers (HCWs) can experience a variety of emotional impacts when responding to disasters and terrorism events. The Anticipate, Plan and Deter (APD) Responder Risk and Resilience Model was developed to provide a new, evidence-informed method for understanding and managing psychological impacts among HCWs. APD includes pre-deployment development of an individualized resilience plan and an in-theater, real-time self-triage system, which together allow HCWs to assess and manage the full range of psychological risk and resilience for themselves and their families. The inclusion of objective mental health risk factors to prompt activation of a coping plan, in connection with unit leadership real-time situational awareness, enables the first known evidence-driven “targeted action” plan to address responder risk early before Post Traumatic Stress Disorder and impairment become established. This paper describes pilot work using the self-triage system component in Alameda County’s Urban Shield and the Philippines’ Typhoon Haiyan, and then reports a case example of the full APD model implementation in West Africa’s Ebola epidemic.

scholarly journals Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Bhargav Appasani ◽  
Amitkumar Vidyakant Jha ◽  
Sunil Kumar Mishra ◽  
Abu Nasar Ghazali
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Area Measurement ◽  
Measurement Unit ◽  
Monitoring And Control ◽  
Communication Infrastructure ◽  
Wide Area Measurement System ◽  
Digital Elevation ◽  
Elevation Model ◽  
And Control

AbstractReal time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

Use of PMU-Based Software Platform to Provide Real-Time Situational Awareness for Bronzeville Community Microgrid

2020 ◽  
Author(s):  
Niroj Gurung ◽  
Sri Raghavan Raghav Kothandaraman ◽  
Liuxi Calvin Zhang ◽  
Heng Kevin Chen ◽  
Farnoosh Rahmatian ◽  
...  
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Software Platform

Post-traumatic Stress and Subthreshold Autism Spectrum Among Divers of the Italian Navy Employed in Search and Rescue Activities

2017 ◽  
Vol 41 (S1) ◽  
pp. S722-S722
Author(s):  
C. Carmassi ◽  
P. Isabella ◽  
C.A. Bertelloni ◽  
M. Corsi ◽  
G. Massimetti ◽  
...  
Keyword(s):  
Social Adjustment ◽  
Traumatic Stress ◽  
Autism Spectrum ◽  
Social Impairment ◽  
Self Report ◽  
Risk And Resilience ◽  
Post Traumatic Stress ◽  
Rescue Operation ◽  
Autism Symptomatology ◽  
Post Traumatic

IntroductionRescue emergency personnel is at high risk to develop PTSD due to possible extreme and repetitive exposition to “cruel details of traumatic events”.ObjectiveThis study aimed to explore posttraumatic stress and subthreshold autism symptomatology and their impact on social and working functioning level among sub mariner of Italian Navy, who were employed in the Costa Concordia and Genova tower rescue operation.MethodsEighty-five subjects were enrolled and investigated by the following instruments: Trauma and Loss Spectrum Self-Report (TALS-SR), Adult Autism Subthreshold Spectrum (AdAS Spectrum) and Work and Social Adjustment Scale (WSAS).ResultsThe response rate was about 50%. Ninety-five percent of the subjects were employed in recovering corpses and 80% reported at least one rescue operation in the last three years. Full and partial DSM-5 PTSD rates were 8% and 27.5%, respectively. A strong correlation emerged between several TALS-SR and ADAS domain. Furthermore, TALS-SR domain scores were related to WSAS domain.ConclusionThis data showed rescue personnel to be at risk for post-traumatic stress spectrum and related work and social impairment. Further studies are needed to better investigate possible risk and resilience factors associated to PTSD.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals An Augmented Warning System for Pedestrians: User Interface Design and Algorithm Development

2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Interface Design ◽  
Situational Awareness ◽  
Warning System ◽  
User Interface Design ◽  
Warning Systems ◽  
Projection Algorithms ◽  
Time Projection ◽  
Timely Warning

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.

A guided latent Dirichlet allocation approach to investigate real-time latent topics of Twitter data during Hurricane Laura

2021 ◽  
pp. 016555152110077
Author(s):  
Sulong Zhou ◽  
Pengyu Kan ◽  
Qunying Huang ◽  
Janet Silbernagel
Keyword(s):  
Social Media ◽  
Real Time ◽  
Language Processing ◽  
Disaster Response ◽  
Domain Knowledge ◽  
Latent Dirichlet Allocation ◽  
Situational Awareness ◽  
High Performing ◽  
Latent Topics ◽  
Dirichlet Allocation

Natural disasters cause significant damage, casualties and economical losses. Twitter has been used to support prompt disaster response and management because people tend to communicate and spread information on public social media platforms during disaster events. To retrieve real-time situational awareness (SA) information from tweets, the most effective way to mine text is using natural language processing (NLP). Among the advanced NLP models, the supervised approach can classify tweets into different categories to gain insight and leverage useful SA information from social media data. However, high-performing supervised models require domain knowledge to specify categories and involve costly labelling tasks. This research proposes a guided latent Dirichlet allocation (LDA) workflow to investigate temporal latent topics from tweets during a recent disaster event, the 2020 Hurricane Laura. With integration of prior knowledge, a coherence model, LDA topics visualisation and validation from official reports, our guided approach reveals that most tweets contain several latent topics during the 10-day period of Hurricane Laura. This result indicates that state-of-the-art supervised models have not fully utilised tweet information because they only assign each tweet a single label. In contrast, our model can not only identify emerging topics during different disaster events but also provides multilabel references to the classification schema. In addition, our results can help to quickly identify and extract SA information to responders, stakeholders and the general public so that they can adopt timely responsive strategies and wisely allocate resource during Hurricane events.

Real-time and near real-time ZTD from a local network of low-cost dual-frequency GNSS receivers.

2021 ◽  
Author(s):  
Tomasz Hadas ◽  
Grzegorz Marut ◽  
Jan Kapłon ◽  
Witold Rohm
Keyword(s):  
Water Vapor ◽  
Real Time ◽  
Low Cost ◽  
Weather Prediction ◽  
Local Network ◽  
System Component ◽  
Dual Frequency ◽  
Lower Accuracy ◽  
Gnss Receivers ◽  
The Impact

<p>The dynamics of water vapor distribution in the troposphere, measured with Global Navigation Satellite Systems (GNSS), is a subject of weather research and climate studies. With GNSS, remote sensing of the troposphere in Europe is performed continuously and operationally under the E-GVAP (http://egvap.dmi.dk/) program with more than 2000 permanent stations. These data are one of the assimilation system component of mesoscale weather prediction models (10 km scale) for many nations across Europe. However, advancing precise local forecasts for severe weather requires high resolution models and observing system.   Further densification of the tracking network, e.g. in urban or mountain areas, will be costly when considering geodetic-grade equipment. However, the rapid development of GNSS-based applications results in a dynamic release of mass-market GNSS receivers. It has been demonstrated that post-processing of GPS-data from a dual-frequency low-cost receiver allows retrieving ZTD with high accuracy. Although low-cost receivers are a promising solution to the problem of densifying GNSS networks for water vapor monitoring, there are still some technological limitations and they require further development and calibration.</p><p>We have developed a low-cost GNSS station, dedicated to real-time GNSS meteorology, which provides GPS, GLONASS and Galileo dual-frequency observations either in RINEX v3.04 format or via RTCM v3.3 stream, with either Ethernet or GSM data transmission. The first two units are deployed in a close vicinity of permanent station WROC, which belongs to the International GNSS Service (IGS) network. Therefore, we compare results from real-time and near real-time processing of GNSS observations from a low-cost unit with IGS Final products. We also investigate the impact of replacing a standard patch antenna with an inexpensive survey-grade antenna. Finally, we deploy a local network of low-cost receivers in and around the city of Wroclaw, Poland, in order to analyze the dynamics of troposphere delay at a very high spatial resolution.</p><p>As a measure of accuracy, we use the standard deviation of ZTD differences between estimated ZTD and IGS Final product. For the near real-time mode, that accuracy is 5 mm and 6 mm, for single- (L1) and dual-frequency (L1/L5,E5b) solution, respectively. Lower accuracy of the dual-frequency relative solution we justify by the missing antenna phase center correction model for L5 and E5b frequencies. With the real-time Precise Point Positioning technique, we estimate ZTD with the accuracy of 7.5 – 8.6 mm. After antenna replacement, the accuracy is improved almost by a factor of 2 (to 4.1 mm), which is close to the 3.1 mm accuracy which we obtain in real-time using data from the WROC station.</p>

scholarly journals Navigation Security Module with Real-Time Voice Command Recognition System

2017 ◽  
Vol 24 (2) ◽  
pp. 17-26
Author(s):  
Mustafa Yagimli ◽  
Huseyin Kursat Tezer
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Predictive Coding ◽  
Recognition System ◽  
Time Warping ◽  
Linear Predictive Coding ◽  
Mel Frequency Cepstral Coefficients ◽  
Voice Command ◽  
Security Module ◽  
Dynamic Time

Abstract The real-time voice command recognition system used for this study, aims to increase the situational awareness, therefore the safety of navigation, related especially to the close manoeuvres of warships, and the courses of commercial vessels in narrow waters. The developed system, the safety of navigation that has become especially important in precision manoeuvres, has become controllable with voice command recognition-based software. The system was observed to work with 90.6% accuracy using Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) parameters and with 85.5% accuracy using Linear Predictive Coding (LPC) and DTW parameters.

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