Ensemble visual analysis architecture with high mobility for large-scale critical infrastructure simulations

2015 ◽  
Author(s):  
Todd Eaglin ◽  
Xiaoyu Wang ◽  
William Ribarsky ◽  
William Tolone
Author(s):  
David Mendonça ◽  
William A. Wallace ◽  
Barbara Cutler ◽  
James Brooks

AbstractLarge-scale disasters can produce profound disruptions in the fabric of interdependent critical infrastructure systems such as water, telecommunications and electric power. The work of post-disaster infrastructure restoration typically requires information sharing and close collaboration across these sectors; yet – due to a number of factors – the means to investigate decision making phenomena associated with these activities are limited. This paper motivates and describes the design and implementation of a computer-based synthetic environment for investigating collaborative information seeking in the performance of a (simulated) infrastructure restoration task. The main contributions of this work are twofold. First, it develops a set of theoretically grounded measures of collaborative information seeking processes and embeds them within a computer-based system. Second, it suggests how these data may be organized and modeled to yield insights into information seeking processes in the performance of a complex, collaborative task. The paper concludes with a discussion of implications of this work for practice and for future research.


2021 ◽  
Vol 12 ◽  
Author(s):  
Ivan Lopez ◽  
Reinaldo Aravena ◽  
Daniel Soza ◽  
Alicia Morales ◽  
Silvia Riquelme ◽  
...  

The Chilean workforce has over 200,000 people that are intermittently exposed to altitudes over 4,000 m. In 2012, the Ministry of Health provided a technical guide for high-altitude workers that included a series of actions to mitigate the effects of hypoxia. Previous studies have shown the positive effect of oxygen enrichment at high altitudes. The Atacama Large Millimeter/submillimeter Array (ALMA) radiotelescope operates at 5,050 m [Array Operations Site (AOS)] and is the only place in the world where pressure swing adsorption (PSA) and liquid oxygen technologies have been installed at a large scale. These technologies reduce the equivalent altitude by increasing oxygen availability. This study aims to perform a retrospective comparison between the use of both technologies during operation in ALMA at 5,050 m. In each condition, variables such as oxygen (O2), temperature, and humidity were continuously recorded in each AOS rooms, and cardiorespiratory variables were registered. In addition, we compared portable O2 by using continuous or demand flow during outdoor activities at very high altitudes. The outcomes showed no differences between production procedures (PSA or liquid oxygen) in regulating oxygen availability at AOS facilities. As a result, big-scale installations have difficulties reaching the appropriate O2 concentration due to leaks in high mobility areas. In addition, the PSA plant requires adequacy and maintenance to operate at a very high altitude. A continuous flow of 2–3 l/min of portable O2 is recommended at 5,050 m.


2022 ◽  
Vol 16 (1) ◽  
pp. 0-0

The Domain Name System - DNS is regarded as one of the critical infrastructure component of the global Internet because a large-scale DNS outage would effectively take a typical user offline. Therefore, the Internet community should ensure that critical components of the DNS ecosystem - that is, root name servers, top-level domain registrars and registries, authoritative name servers, and recursive resolvers - function smoothly. To this end, the community should monitor them periodically and provide public alerts about abnormal behavior. The authors propose a novel quantitative approach for evaluating the health of authoritative name servers – a critical, core, and a large component of the DNS ecosystem. The performance is typically measured in terms of response time, reliability, and throughput for most of the Internet components. This research work proposes a novel list of parameters specifically for determining the health of authoritative name servers: DNS attack permeability, latency comparison, and DNSSEC validation.


2020 ◽  
Author(s):  
Shimpei Uesawa ◽  
Kiyoshi Toshida ◽  
Shingo Takeuchi ◽  
Daisuke Miura

Abstract Tephra falls can disrupt critical infrastructure, including transportation and electricity networks. Probabilistic assessments of tephra fall hazards have been performed using computational techniques, but it is also important to integrate long-term, regional geological records. To assess tephra fall load hazards in Japan, we re-digitized an existing database of 551 tephra distribution maps. We used the re-digitized datasets to produce hazard curves for a range of tephra loads for various localities. We calculated annual exceedance probabilities (AEPs) and constructed hazard curves from the most complete part of the geological record. We used records of tephra fall events with a Volcanic Explosivity Index (VEI) of 4–7 (based on survivor functions) that occurred over the last 150 ka, as the database contains a very high percentage (around 90%) of VEI 4–7 events for this period. We fitted the data for this period using a Poisson distribution function. Hazard curves were constructed for the tephra fall load at 47 prefectural offices throughout Japan, and four broad regions were defined (NE–W, NE–E, W, and SW Japan). AEPs were relatively high, exceeding 1 × 10 −4 for loads greater than 0 kg/m 2 on the eastern (down-wind) side of the volcanic front in the NE–E region. In much of the W and SW regions, maximum loads were heavier, but AEPs were lower (<10 −4 ). Tephras from large (VEI ≥ 6) events are the predominant hazard in every region. A parametric analysis was applied to investigate regional variability using AEP diagrams and slope shape parameters via curve fitting with exponential and double-exponential decay functions. Two major differences were recognized between the hazard curves from borehole data and those from the digitized tephra database. The first is a significant underestimation of AEP for frequent events using the tephra database, by one to two orders of magnitude. This is explained in terms of the lack of records for smaller tephra fall events in the database. The second is an overestimation of the heaviest tephra load events, which differ by a factor of two to three. This difference might be due to the tephra fall distribution contour interpolation methodology used to generate the original database. The hazard curve for Tokyo developed in this study differs from those that have been generated previously using computational techniques. For the Tokyo region, the probabilities and tephra loads produced by computational methods are at least one order of magnitude greater than those generated during the present study. These discrepancies are inferred to have been caused by initial parameter settings in the computational simulations, including their incorporation of large-scale eruptions of up to VEI = 7 for all large stratovolcanoes, regardless of their eruptive histories. To improve the precision of the digital database, we plan to incorporate recent (since 2003) tephra distributions, revise questionable isopach maps, and develop an improved interpolation method for digitizing tephra fall distributions.


Author(s):  
W. Treurniet

Given its nature, a crisis has a significant community impact. This applies in particular to emergencies: crises that arise quickly. Because of the complex and multifaceted nature of large-scale incidents, the response requires coordinated effort by multiple organizations. This networked collaboration is not solely restricted to professional organizations. In responding to an incident, the affected community can itself be an important source of information and capabilities. This chapter discusses how one can shape a trustworthy and decisive response organization in which relevant and useful capacities available in the community are incorporated. This discussion has two focal points. The first focal point is the role of the affected community in the case of an emergency. On the one hand, an emergency affects the fabric of the community, such as the critical infrastructure. On the other, a community has inherent internal resources that give it resilience and capacity to respond in a crisis. This needs to be reflected in the choice of emergency response planning model. The second focal point is the structure of the emergency response network. An emergency response network is a mixed-sector network. This means that coordination is needed among organizations and collectives with differing strategic orientations.


2012 ◽  
Vol 31 (3pt3) ◽  
pp. 1175-1184 ◽  
Author(s):  
A. Lex ◽  
M. Streit ◽  
H.-J. Schulz ◽  
C. Partl ◽  
D. Schmalstieg ◽  
...  

2019 ◽  
Vol 13 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Amy Helene Schnall ◽  
Joseph (Jay) Roth ◽  
Lisa LaPlace Ekpo ◽  
Irene Guendel ◽  
Michelle Davis ◽  
...  

AbstractObjectivesTwo Category 5 storms, Hurricane Irma and Hurricane Maria, hit the U.S. Virgin Islands (USVI) within 13 days of each other in September 2017. These storms caused catastrophic damage across the territory, including widespread loss of power, destruction of homes, and devastation of critical infrastructure. During large scale disasters such as Hurricanes Irma and Maria, public health surveillance is an important tool to track emerging illnesses and injuries, identify at-risk populations, and assess the effectiveness of response efforts. The USVI Department of Health (DoH) partnered with shelter staff volunteers to monitor the health of the sheltered population and help guide response efforts.MethodsShelter volunteers collect data on the American Red Cross Aggregate Morbidity Report form that tallies the number of client visits at a shelter’s health services every 24 hours. Morbidity data were collected at all 5 shelters on St. Thomas and St. Croix between September and October 2017. This article describes the health surveillance data collected in response to Hurricanes Irma and Maria.ResultsFollowing Hurricanes Irma and Maria, 1130 health-related client visits were reported, accounting for 1655 reasons for the visits (each client may have more than 1 reason for a single visit). Only 1 shelter reported data daily. Over half of visits (51.2%) were for health care management; 17.7% for acute illnesses, which include respiratory conditions, gastrointestinal symptoms, and pain; 14.6% for exacerbation of chronic disease; 9.8% for mental health; and 6.7% for injury. Shelter volunteers treated many clients within the shelters; however, reporting of the disposition (eg, referred to physician, pharmacist) was often missed (78.1%).ConclusionShelter surveillance is an efficient means of quickly identifying and characterizing health issues and concerns in sheltered populations following disasters, allowing for the development of evidence-based strategies to address identified needs. When incorporated into broader surveillance strategies using multiple data sources, shelter data can enable disaster epidemiologists to paint a more comprehensive picture of community health, thereby planning and responding to health issues both within and outside of shelters. The findings from this report illustrated that managing chronic conditions presented a more notable resource demand than acute injuries and illnesses. Although there remains room for improvement because reporting was inconsistent throughout the response, the capacity of shelter staff to address the health needs of shelter residents and the ability to monitor the health needs in the sheltered population were critical resources for the USVI DoH overwhelmed by the disaster. (Disaster Med Public Health Preparedness. 2019;13:38-43)


Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1747
Author(s):  
Hansaka Angel Dias Edirisinghe Kodituwakku ◽  
Alex Keller ◽  
Jens Gregor

The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection.


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