课题基金 / 基金详情

CNIC:US-UAE Planning Visit: Development of Research Collaborations on Spatio-temporal Modeling and Analysis of Mobile Sensor Data in Evaluating Environmental Exposures

CNIC:US-UAE Planning Visit: Development of Research Collaborations on Spatio-temporal Modeling and Analysis of Mobile Sensor Data in Evaluating Environmental Exposures
CNIC:美国-阿联酋计划访问:评估环境暴露的移动传感器数据时空建模和分析方面的研究合作的发展
批准号:
1338378
负责人:
Wan Bae
金额:
$3.46万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2014-09-30
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项目摘要

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中文摘要
翻译
1338378Bae该项目将支持威斯康星大学梅诺莫尼分校的万·贝博士领导的一个团队对阿拉伯联合酋长国(UAE)进行为期两周的访问,以便在两国的研究人员之间建立新的国际研究合作。这次访问将使国际和平组织和刘成博士以及来自UWI-Stout的两名本科生-丹佛大学的Petr Vojtchovsky博士和明尼苏达大学的Shashi Shekhar博士会见来自阿拉伯联合酋长国大学的Shayma Alkobaisi博士、Ahmed Al Faresi博士、Mohammad Masud博士、Fatma Maskari博士和他们的学生,以及来自沙迦大学的Ibrahim Kamel博士,以建立一个研究框架,对个人对各种环境条件的暴露进行建模和分析。这项研究将专注于开发数据模型和计算算法,以有效地映射个人?环境暴露于他们的健康状况,并实施地图/减少方法,以有效地处理拟议模型和算法的迭代计算。因此,研究小组将提交一份针对NSF智能健康和福祉(SHB)计划的后续拨款提案。智力价值:在几项大规模暴露研究中,已经发现了哮喘和肺癌等负面健康影响与空气污染、烟草烟雾和湿度等环境因素水平上升之间的关系。评估环境暴露通常需要跟踪、监控、存储和分析个人的移动轨迹以及个人所暴露的几个环境条件,以便确定这些数据之间的关系。由于时空不确定性、数据大小以及诸如反向传播神经网络算法等常用数据建模算法的迭代计算,出现了挑战。这项研究的主要目标是:(1)开发新的数据模型来绘制个人环境暴露于健康水平的地图,(2)设计一种新的技术来在Hadoop系统的Map/Reduce范式上实现所提出的模型,(3)开发数据分析算法来表征学习模型中的行为并解释数据以估计其对人类健康的影响,(4)建立哮喘患者的评估系统作为案例研究。该研究团队由数学家、计算机和信息科学家、工程师和医学专家组成,有能力执行计划的任务。广泛的影响:该项目将支持两名美国本科生积极参与科学研究。他们的参与旨在通过各种活动将研究和教育结合起来。获得跨文化合作的经验对美国和阿联酋的学生来说都是互惠互利的。该项目还促进了多样性,来自美国的学生可能是第一代大学生和阿联酋国家学生。美国和阿联酋的研究人员将建立新的关系,为未来在研究和教育方面的合作奠定基础。此外,该项目将扩大对环境对公共健康的影响以及以个人为基础的医疗保健对患者、医生和医疗保健提供者的重要性的理解。
英文摘要
1338378BaeThis project will support a team headed by Dr. Wan Bae, University of Wisconsin-Stout, Menomonie, WI for a two week visit to the United Arab Emirates (UAE) for the establishment of new international research collaborations between researchers in the two countries. This visit will enable the PI and Dr. Cheng Liu and two undergraduate students from the UWI-Stout, Dr. Petr Vojtchovsky from the University of Denver, and Dr. Shashi Shekhar from the University of Minnesota, to meet with Dr. Shayma Alkobaisi, Dr. Ahmed Al Faresi, Dr. Mohammad Masud, Dr. Fatma Maskari and their students from the United Arab Emirates University, and Dr. Ibrahim Kamel from the University of Sharjah to develop a research framework for modeling and analysis of individual exposure to various environmental conditions. The research will focus on developing data models and computing algorithms for effectively mapping individuals? environmental exposure to their health conditions, and implementing Map/Reduce methods for efficiently processing iterative computations of the proposed models and algorithms. As a result, the research team will submit a subsequent grant proposal targeted for the NSF Smart Health and Wellbeing (SHB) program.Intellectual Merit: Relations between negative health effects like asthma and lung cancer and elevated levels of the environmental factors, such as air pollution, tobacco smoke and humidity, have been detected in several large scale exposure studies. Evaluating environmental exposures often requires the ability to track, monitor, store, and analyze individual moving trajectories along with several environmental conditions the individual is exposed to in order to identify relationships among these data. Challenges arise due to spatio-temporal uncertainty, data size, and iterative computations of commonly used data modeling algorithms such as the Back propagation neural network algorithm. The main objectives of this research are: (1) to develop novel data models to map individuals environmental exposures to health levels, (2) to design a new technique for implementing the proposed models on the Map/Reduce paradigm of the Hadoop system, (3) to develop data analysis algorithms to characterize behaviors in learned models and interpret the data for estimating their effects on human health, (4) to build an evaluation system for Asthma patients as a case study. The research team, consisting of mathematicians, computer and information scientists, engineers and medical expertise, is capable of carrying out the planned tasks.Broader Impacts: The project will support two U.S. undergraduate students to be actively involved in scientific research. Their involvement is designed to integrate research and education through various activities. Gaining experience with inter-cultural collaboration is one of the mutual benefits to both the U.S. and UAE students. The also promotes diversity with the involvement by students from the U.S. who may be first-generation college students and UAE national students. The U.S. and UAE researchers will build new relationships that are the basis for future collaborations in research and education. Further, this project will broaden the understanding of the impact of the environment on public health and the importance of individual-based health care for patients, doctors, and healthcare providers.
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