scholarly journals Detection of Human Under Earthquake Rubble

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3391-3394
Keyword(s):  
Volcanic Eruptions ◽  
Robotic Platform ◽  
Newspaper Report ◽  
Location Mapping ◽  
Live Interaction

Natural calamities like earthquake,flood ,volcanic eruptions , landslides ,avalanches ,etc are unavoidable circumstances .Occurance of such natural ailments is unpredictablecausing huge damageto resources and structures which is unavoidable .Measurement, eleventh hour detection, precautionary and rescue methods are onlypossible options .A proper rescue can do milestones in savinglife of people under such circumstances. In messina region of Newyork death tolls were 5000 during earthquake, nearly halfthe population. In Utharkhand during 2013 a landslide caused lots of people buried under earth. Newspaper report stated that if people were detected earlier death tolls would have been quite low. In this paper we design a rescue robotic platform which can act more quickly in detection location mapping diagnosing status post earthquake, avalanches andlandslides. The robot platformdesigned isfor disastermanagementsystemduringavalanches ,earthquakes , and landslidesfor accurate andfasterdetectionofhuman trapped inside without live interaction and notcausingdamagedue to increasedload of rescuer onthemwhiledetectionusinga robotic platformcontrolled remotely

A Natural Language Processing Pipeline to Identify COVID-19 Outbreaks from Contact Tracing Interview Forms (Preprint)

2022 ◽  
Author(s):  
John Caskey ◽  
Iain L McConnell ◽  
Madeline Oguss ◽  
Dmitriy Dligach ◽  
Rachel Kulikoff ◽  
...  
Keyword(s):  
Language Processing ◽  
Disease Surveillance ◽  
Language Model ◽  
Entity Recognition ◽  
Contact Tracing ◽  
Free Text ◽  
Local Health ◽  
Targeted Interventions ◽  
Mapping Tool ◽  
Location Mapping

BACKGROUND In Wisconsin, COVID-19 case interview forms contain free text fields that need to be mined to identify potential outbreaks for targeted policy making. We developed an automated pipeline to ingest the free text into a pre-trained neural language model to identify businesses and facilities as outbreaks. OBJECTIVE We aim to examine the performance of our pipeline. METHODS Data on cases of COVID-19 were extracted from the Wisconsin Electronic Disease Surveillance System (WEDSS) for Dane County between July 1, 2020, and June 30, 2021. Features from the case interview forms were fed into a Bidirectional Encoder Representations from Transformers (BERT) model that was fine-tuned for named entity recognition (NER). We also developed a novel location mapping tool to provide addresses for relevant NERs. The pipeline was validated against known outbreaks that were already investigated and confirmed. RESULTS There were 46,898 cases of COVID-19 with 4,183,273 total BERT tokens and 15,051 unique tokens. The recall and precision of the NER tool were 0.67 (95 % CI 0.66-0.68) and 0.55 (95 % CI: 0.54-0.57), respectively. For the location mapping tool, the recall and precision were 0.93 (95% CI: 0.92-0.95) and 0.93 (95% CI: 0.92-0.95), respectively. Across monthly intervals, the NER tool identified more potential clusters than were confirmed in the WEDSS system. CONCLUSIONS We developed a novel pipeline of tools that identified existing outbreaks and novel clusters with associated addresses. Our pipeline ingests data from a statewide database and may be deployed to assist local health departments for targeted interventions. CLINICALTRIAL Not applicable

Gully location mapping at a national scale for South Africa

2012 ◽  
Vol 94 (2) ◽  
pp. 208-218 ◽  
Author(s):  
N. Mararakanye ◽  
J. J. Le Roux
Keyword(s):  
South Africa ◽  
National Scale ◽  
Location Mapping

scholarly journals Systematic Protein Location Mapping Reveals Five Principal Chromatin Types in Drosophila Cells

Cell ◽  
2011 ◽  
Vol 145 (1) ◽  
pp. 160 ◽  
Author(s):  
Guillaume J. Filion ◽  
Joke G. van Bemmel ◽  
Ulrich Braunschweig ◽  
Wendy Talhout ◽  
Jop Kind ◽  
...  
Keyword(s):  
Protein Location ◽  
Location Mapping ◽  
Drosophila Cells

scholarly journals THE MAPPING OF SUBSURFACE TEMPERATURE AND STUDY OF GEOTHERMAL GRADIENT ANOMALY IN THE DISCHARGE AREA IN NORTH SULAWESI

2020 ◽  
Vol 6 (1) ◽  
pp. 1-4
Author(s):  
Donny Royke Wenas ◽  
Cyrke A.N. Bujung
Keyword(s):  
Heat Source ◽  
Geothermal Gradient ◽  
Heat Propagation ◽  
Source Zone ◽  
Maximum Temperature ◽  
Heat Transmission ◽  
North Sulawesi ◽  
Subsurface Layers ◽  
Remote Sensing Techniques ◽  
Location Mapping

The aim of this research is to measure and mapping the temperature distribution in several subsurface layers in the manifestation of geothermal warm ground and steaming ground, and analyze the geothermal subsurface gradient, to determine the heat source zone, and the pattern and direction of heat flow from subsurface to surface in  Hydrothermal area of Minahasa Indonesia. The method used is direct measurement in the field. To determine the coordinates of geothermal manifestations and location mapping, using remote sensing techniques. The results showed that at a depth of 200 cm the temperature reaches 102 0C and the heat source comes from the northeast and from the south. At a depth of 150 cm the temperature varies from 52 to 100 0C with an even distribution in almost every direction. At a depth of 50 to 100 cm the maximum temperature reaches 98 0C with heat propagation starting to concentrate then northeast, and then out to the surface in the northeast. The pattern of heat transmission is almost linear along with the geothermal gradient.

scholarly journals Location Mapping And Tsunami Disaster Evacuation Pathway Using Dijkstra Algorithm In Kota Sigli District, Pidie District

2019 ◽  
Vol 6 (2) ◽  
pp. 748 ◽  
Author(s):  
Husna Maulida ◽  
Faisal Faisal ◽  
Teuku Alvisyahrin
Keyword(s):  
Secondary Data ◽  
Primary Data ◽  
Topographic Map ◽  
Dijkstra Algorithm ◽  
Contour Map ◽  
Tsunami Disaster ◽  
Vertical Evacuation ◽  
Paved Road ◽  
Location Mapping ◽  
2004 Tsunami

Sigli City Sub District is one of the Sub Districts affected by the 2004 tsunami. At that time, the community did not understand the danger of the tsunami and did not understand how to save themselves. The purpose of this study was to identify and to map out effective tsunami evacuation locations and routes in Sigli City Sub District using Dijkstra algorithm. Primary data (tsunami inundation) for this study were obtained from interviews with community representatives involving 32 people in 16 villages. Administrative map, topographic map, population density map, contour map and land use map (secondary data) were obtained from relevant institutions. The results of the study indicate that horizontal evacuation can be done through available paved road living the coastal area towads 4 recommended locations based on the physical feasibility of the land. For vertical evacuation, 24 buildings available in 7 villages can be recommended, on the condition that their structural feasibility and access standard are met.

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