A Big Data Approach to Support Information Distribution in Crisis Response

Author(s):  
Niels Netten ◽  
Susan van den Braak ◽  
Sunil Choenni ◽  
Maarten van Someren
Author(s):  
Mohamed Elsotouhy ◽  
Geetika Jain ◽  
Archana Shrivastava

The concept of big data (BD) has been coupled with disaster management to improve the crisis response during pandemic and epidemic. BD has transformed every aspect and approach of handling the unorganized set of data files and converting the same into a piece of more structured information. The constant inflow of unstructured data shows the research lacuna, especially during a pandemic. This study is an effort to develop a pandemic disaster management approach based on BD. BD text analytics potential is immense in effective pandemic disaster management via visualization, explanation, and data analysis. To seize the understanding of using BD toward disaster management, we have taken a comprehensive approach in place of fragmented view by using BD text analytics approach to comprehend the various relationships about disaster management theory. The study’s findings indicate that it is essential to understand all the pandemic disaster management performed in the past and improve the future crisis response using BD. Though worldwide, all the communities face big chaos and have little help reaching a potential solution.


Author(s):  
Junaid Qadir ◽  
Anwaar Ali ◽  
Raihan ur Rasool ◽  
Andrej Zwitter ◽  
Arjuna Sathiaseelan ◽  
...  
Keyword(s):  
Big Data ◽  

2020 ◽  
Vol 102 (913) ◽  
pp. 75-94
Author(s):  
Theodora Gazi ◽  
Alexandros Gazis

AbstractThe COVID-19 pandemic has served as a wake-up call for humanitarian aid actors to reconsider data collection methods, as old ways of doing business become increasingly obsolete. Although access to information on the affected population is critical now more than ever to support the pandemic response, the limitation of aid workers’ presence in the field imposes hard constraints on relief projects. In this article, we consider how aid actors can use “big data” as a crisis response tool to support humanitarian projects, in cases when the General Data Protection Regulation is applicable. We also provide a framework for examining open-source platforms, and discuss the advantages and privacy challenges of big data.


2022 ◽  
Vol 13 (1) ◽  
pp. 1-21
Author(s):  
Zhihan Lv ◽  
Ranran Lou ◽  
Hailin Feng ◽  
Dongliang Chen ◽  
Haibin Lv

Two-dimensional 1 arrays of bi-component structures made of cobalt and permalloy elliptical dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a self-aligned shadow deposition technique. Brillouin light scattering has been exploited to study the frequency dependence of thermally excited magnetic eigenmodes on the intensity of the external magnetic field, applied along the easy axis of the elements. Scientific information technology has been developed rapidly. Here, the purposes are to make people's lives more convenient and ensure information management and classification. The machine learning algorithm is improved to obtain the optimized Light Gradient Boosting Machine (LightGBM) algorithm. Then, an Android-based intelligent support information management system is designed based on LightGBM for the big data analysis and classification management of information in the intelligent support information management system. The system is designed with modules of employee registration and login, company announcement notice, attendance and attendance management, self-service, and daily tools with the company as the subject. Furthermore, the performance of the constructed information management system is analyzed through simulations. Results demonstrate that the training time of the optimized LightGBM algorithm can stabilize at about 100s, and the test time can stabilize at 0.68s. Besides, its accuracy rate can reach 89.24%, which is at least 3.6% higher than other machine learning algorithms. Moreover, the acceleration efficiency analysis of each algorithm suggests that the optimized LightGBM algorithm is suitable for processing large amounts of data; its acceleration effect is more apparent, and its acceleration ratio is higher than other algorithms. Hence, the constructed intelligent support information management system can reach a high accuracy while ensuring the error, with apparent acceleration effect. Therefore, this model can provide an experimental reference for information classification and management in various fields.


ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


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