首页> 外文会议>International Conference on Electrical, Computer and Communication Technologies >Prevention of infectious disease based on big data analytics and map-reduce
【24h】

Prevention of infectious disease based on big data analytics and map-reduce

机译:基于大数据分析和地图缩减的传染病预防

获取原文

摘要

The rapid increase in population creates an issue in handling and analyzing the population data for the traditional data base management system. So Big data came into figure to solve the issue. The main components of Big data are Hadoop and Map-Reduce. Big data is more efficient in comparison to the traditional data base system due to some of its basic features like Velocity, Veracity, Volume, Verity and Value. Infectious disease is the illness resulting from infection. This is caused by infectious agents including Viruses, Prions, Bacteria, Nematodes etc. Population dynamics is a branch of life science which includes the study of population size and age composition of dynamic system and the biological and environmental process managing them. This proposed paper consider the Dengue Fever as an infectious disease and divides the population dynamic into three parts i.e. High Vulnerable, Mid vulnerable, Low vulnerable to Dengue. And also suggest the preventive measure respectively like Forced preventive for high vulnerable, Efficient preventive measure for mid vulnerable and delayed preventive measure for low vulnerable areas by utilizing the benefits of big data.
机译:人口的快速增长在处理和分析传统数据库管理系统的人口数据方面造成了一个问题。因此,大数据应运而生,以解决该问题。大数据的主要组件是Hadoop和Map-Reduce。与传统数据库系统相比,大数据由于其一些基本功能(例如速度,准确性,容量,有效性和价值)而效率更高。传染病是由感染引起的疾病。这是由包括病毒,Pr病毒,细菌,线虫等传染因子引起的。种群动态是生命科学的一个分支,其中包括研究种群的大小和动态系统的年龄组成以及管理它们的生物学和环境过程。本文提议将登革热视为一种传染病,并将人口动态分为三个部分,即高危人群,中度脆弱人群,低度易感染登革热人群。并分别利用大数据的优势,提出了针对高脆弱人群的强制预防,针对中脆弱人群的有效预防措施和针对低脆弱人群的延迟预防措施等预防措施。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号