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2021 ◽  
Vol 17 (9) ◽  
Author(s):  
Seán I O’Donoghue ◽  
Andrea Schafferhans ◽  
Neblina Sikta ◽  
Christian Stolte ◽  
Sandeep Kaur ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4840
Author(s):  
Roi Yozevitch ◽  
Revital Marbel ◽  
Nir Flysher ◽  
Boaz Ben-Moshe

Global Navigation Satellite Systems (GNSS) jamming is an acute problem in the world of modern navigation. As more and more applications rely on GNSS for both position and timing, jamming ramifications are becoming more severe. In this paper we suggest a novel framework to cope with these threats. First, a Bayesian jamming detection algorithm is introduced. The algorithm can both detect and track several jammers in a pre-defined region of interest. Then, a jamming coverage map algorithm is offered. Similar to cellular 3G/4G coverage maps, such a map can detect “weak” GNSS reception spots and handle them. Since jamming interference can be a dynamic phenomenon (e.g., a vehicle equipped with a jammer), the coverage map changes with time. Thus, interference patterns can be detected more easily. Utilizing the offered algorithm, both on simulation and field experiments, we have succeeded to localize an arbitrary jammer(s) within the region of interest. Thus, the results validate the viability of the proposed method.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
P. G. Sudheesh ◽  
Jaap van de Beek

Under the umbrella of 1G to 5G, different technologies have been used to provide mobile communication. Various technologies are being proposed to bring a person in remote area under coverage. However, a statistical analysis on what these users get from already existing technologies has not been carried out. We fill this gap by carrying out such a study using a measurement campaign, where we present a framework for analyzing mobile signal strength experienced at the user end. Measurements are taken throughout the Norrbotten county, the northernmost county in Sweden, using mobile phones recording various parameters at regular intervals. Based on measured signal strength, a coverage map has been made via inverse distance weighting (IDW) interpolation. Based on the coverage map, various analyses are carried out on signal strength over residential areas and roads of Norrbotten. Overall, we lay a framework to analyze and quantify the effect of signal strength on users.


Author(s):  
Seán I. O’Donoghue ◽  
Andrea Schafferhans ◽  
Neblina Sikta ◽  
Christian Stolte ◽  
Sandeep Kaur ◽  
...  

AbstractIn response to the COVID-19 pandemic, many life scientists are focused on SARS-CoV-2. To help them use available structural data, we systematically modeled all viral proteins using all related 3D structures, generating 872 models that provide detail not available elsewhere. To organise these models, we created a structural coverage map: a novel, one-stop visualization summarizing what is — and is not — known about the 3D structure of the viral proteome. The map highlights structural evidence for viral protein interactions, mimicry, and hijacking; it also helps researchers find 3D models of interest, which can then be mapped with UniProt, PredictProtein, or CATH features. The resulting Aquaria-COVID resource (https://aquaria.ws/covid) helps scientists understand molecular mechanisms underlying coronavirus infection. Based on insights gained using our resource, we propose mechanisms by which the virus may enter immune cells, sense the cell type, then switch focus from viral reproduction to disrupting host immune responses.SignificanceCurrently, much of the COVID-19 viral proteome has unknown molecular structure. To improve this, we generated ∼1,000 structural models, designed to capture multiple states for each viral protein. To organise these models, we created a structure coverage map: a novel, one-stop visualization summarizing what is — and is not — known about viral protein structure. We used these data to create an online resource, designed to help COVID-19 researchers gain insight into the key molecular processes that drive infection. Based on insights gained using our resource, we speculate that the virus may sense the type of cells it infects and, within certain cells, it may switch from reproduction to disruption of the immune system.


2020 ◽  
Author(s):  
Mark Suprenant ◽  
Anuraag Gopaluni ◽  
Meredith Dyson ◽  
Fauzia Shafique ◽  
Muhammad Zaman

Abstract IntroductionThe ongoing war in Yemen continues to pose challenges for health care workers in the country. The fighting has destroyed public infrastructure including primary and secondary health care facilities, hindered the movement of people, food, fuel, medical supplies, and information, and restricted access to and availability of social services including safe drinking water and sanitation. This has led to the increase in the spread of diarrheal diseases, including cholera, which, despite the efficacy of zinc and oral rehydration salt solutions to treat the resulting dehydration, remains one of greatest sources of mortality in children under five years old. In contexts such as Yemen, Health Management Information Systems and Surveillance Systems are weak and unreliable to begin with, with conflict and linked disruption of social services these systems are further weakened making monitoring of the situation and evidence-based planning and implementation even more difficult. Without information on the total number of children suffering from these diseases, it is difficult for health officials and aid organizations to make policy level decisions, inform annual and humanitarian response plans, set targets, mobilize resources, order supplies, deploy resources (human and supplies) and monitor based on needs, leading to poor quality decisions. These reasons, coupled with lack of access, security, and financial and human resources make it even more important in conflict settings, than in non-conflict settings, to know where it is best to invest. This manuscript looks at the development of a computational model designed to draw upon available health data and supplement it with additional sources and acceptable assumptions to provide some of the missing data via health access chart to better inform decision making on the above-mentioned policies. This chart is designed to show what percentage of the total estimated sick population is receiving medical assistance without the need for health workers to place themselves in the way of any additional harm.MethodsA Markov model, which is a probabilistic model that shows how a population moves between different states overtime, was created based on an analysis of Yemen clinical register data from the Ministry of Public Health collected through a third party hired for monitoring purposes covering the period of May through September of 2018. The model was designed with four states for children to transition between over a weekly basis. The probability that a child transitioned from the Sick state to the In-treatment state during any given week was a time varying function based on the average precipitation recorded monthly for 115 years and the state of the roads and bridges during that week as assessed by the World Food Program. The model examined the number of children treated, incidence rate, mortality rate, treatment efficacy and treatment mortality. Once validated, the model was run for 2019 to provide the weekly estimated coverage of children being treated for diarrheal diseases throughout all of Yemen. ResultsThe model was able to recreate the observed trends in treatment on the ground with no significant difference between model output and provided validation data for all metrics. When combined with infrastructure data, the curve of best fit created for the precipitation values depicted a seasonal increase in the number of estimated new diarrheal cases in children under five and a resulting decreasing in the number receiving treatment. This combination has led predictions for the percent coverage to range between an average weekly minimum of 1.73% around the 28th week of the year to a weekly maximum weekly coverage of just over 5% around the new year. ConclusionThe model created and presented in this manuscript shows a seasonal trend in the spread of diarrheal disease in children under five living in Yemen. Despite the assistance of aid organizations in attending to those in need, during the mid-year rains up to 98% are unable to receive medical aid. The coverage map indicates that community outreach or other types of assistance where aid proactively goes out to those in need should be scaled up during and just prior to these periods. This would serve to offset the decrease in the number receiving treatment by lessening the prohibitive travel burden on families during these times.


2020 ◽  
Vol 26 (4) ◽  
Author(s):  
Leonardo Scharth Loureiro Silva ◽  
Silvana Philippi Camboim

Abstract: Cartographic data represents the main and basic component of a Spatial Data Infrastructure. SDI, in turn, has the role of supporting, with strategic information, the most diverse political and economic actions, in the management and planning of public actions. Thus, this work aims, initially, to present an overview of cartography in Brazil through the analysis of the evolution of topographic mapping coverage in the country. For each of the main scales used, a coverage map was created. The analyzes reflect three different periods (until 1997, between 1998 and 2007, after 2008) in order to relate how and to what degree, the creation of Brazilian National SDI (in 2008) had an impact on the mapping production in the country. Given the current panorama, as a final objective, this paper aims at to present proposals to leverage the coverage of this reference data. One of them is the use of new data sources such as Volunteered Geographic Information, especially in areas with outdated mapping or without mapping, as has already been used in some countries. Another proposition is to share the responsibility of mapping through partnerships with other levels of government, which would result the decentralization and the optimization of cartographic production.


Author(s):  
H. R. D. Filgueiras ◽  
E. S. Lima ◽  
T. H. Brandao ◽  
S. Arismar Cerqueira
Keyword(s):  

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 80767-80777 ◽  
Author(s):  
Yaxi Liu ◽  
Wei Huangfu ◽  
Haijun Zhang ◽  
Keping Long

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