Phase I IUCRC University of Maryland Baltimore County: Center for Accelerated Real Time Analytics (CARTA)
Phase I IUCRC University of Maryland Baltimore County: Center for Accelerated Real Time Analytics (CARTA)
批准号:
1747724
负责人:
Karuna Joshi
金额:
$75.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
未结题
起止时间:
2018-06-01 至 2025-05-31
中文摘要
几乎每个研究领域和行业都在努力从大量动态数据中及时提取有用的信息。开发实时和加速分析领域的工具和技术有助于促进科学进步,促进国家繁荣和福利。这一领域的成功取决于平衡基础研究、技术诀窍和商业市场情报。为了应对这一挑战,该项目将行业成员与学术中心联合起来,开展多学科科学和研究,从海量和移动数据中提取价值,并对复杂的动态数据进行更好的决策。加速真实的时间分析中心(CARTA)项目探索了利用相对高风险的基本面发展来帮助组织进行长期、更复杂的分析需求。CARTA的重点是横向基础技术,这些技术将创建能够为国家重要应用提供动力的基础设施。在这种情况下,在巴尔的摩县的马里兰州大学(UMBC),CARTA/UMBC站点将专注于开发下一代认知/自学系统,该系统将利用高性能计算和量子计算平台,以促进实时关键决策。拥有这些技术和系统将是实现整个CARTA中心目标的关键。CARTA中心工作的更广泛影响将是满足行业和社会未来先进的实时分析需求。CARTA开发的技术可以应用于各个行业,包括国家安全、医疗保健、制造业、能源和商业智能。在CARTA所做的基础研究将转化为技术开发,为难题提供实用的解决方案。分析行业的这种范式转变的最终成功将取决于CARTA大学是否有能力培养专家,利用科学和技术解决各种现实生活中的应用。CARTA研究可能涉及敏感的学术和工业数据沿着公共领域数据。 这些数据和由此产生的研究成果将在CARTA结束后的三年内使用每类数据的适当最佳做法予以保留。 将在https://carta.umbc.edu上建立一个中央存储库,适当标记以进行适当的参考和记录,以维护从中心项目中获取和生成的数据。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Nearly every research field and industry sector is struggling with extracting useful information from massive and dynamic data in a timely way. Developing tools and technologies in this realm of real-time and accelerated analytics contributes to promoting the progress of science and to advancing the national prosperity and welfare. Success in this realm hinges on balancing fundamental research, technological know-how, and commercial market intelligence. To address this challenge, this project joins industry members with academic centers to conduct multidisciplinary science and research towards extracting value from massive and moving data and enabling better decision making of complex, dynamic data.The Center of Accelerated Real Time Analytics (CARTA) project explores the ways in which relatively high-risk fundamental developments can be leveraged to help organizations that have longer-term, more complex analytic needs. The focus of CARTA is on horizontal foundational technologies that would create an infrastructure capable of powering applications of national significance. In this context, at University of Maryland, Baltimore County (UMBC), the CARTA/UMBC site will focus on developing next generation cognitive/self-learning systems that will leverage high performance computing and quantum computing platforms, to facilitate real-time critical decision making. Having these technologies and systems will be key in achieving the goals of the overall CARTA center.The broader impact of the work of the CARTA center will be in addressing the future advanced, real-time analytics needs of the industry and society. The techniques developed by CARTA can be applied across industry sectors, including national security, healthcare, manufacturing, energy, and business intelligence. The fundamental research done at CARTA will be translated into technology developments, delivering practical solutions to hard problems. The ultimate success of this paradigm shift by the analytics industry will rest on the ability of CARTA universities to prepare experts to take advantage of the science and technologies to solve a variety of real-life applications.CARTA research may involve sensitive academic and industrial data along with public domain data. This data and resulting research outputs will be maintained using appropriate best practices for each type of data for a period of three years after the closing of CARTA. A central repository, suitably tagged for appropriate referencing and documentation, will be set up at https://carta.umbc.edu for maintaining the acquired and generated data from Center projects. Project results will be made available in response to approved user requests.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Automating Privacy Compliance Using Policy Integrated Blockchain
使用策略集成区块链自动化隐私合规
DOI:
10.3390/cryptography3010007
发表时间:
2019
期刊:
Cryptography
影响因子:
1.6
作者:
[Joshi, Karuna Pande, Banerjee, Agniva]
通讯作者:
Banerjee, Agniva
ViCLOUD: Measuring Vagueness in Cloud Service Privacy Policies and Terms of Services
ViCLOUD:衡量云服务隐私政策和服务条款的模糊性
DOI:
10.1109/cloud49709.2020.00023
发表时间:
2020
期刊:
2020 IEEE 13th International Conference on Cloud Computing (CLOUD
影响因子:
--
作者:
[Kotal, Anantaa, Joshi, Karuna Pande, Joshi, Anupam]
通讯作者:
Joshi, Anupam
An Integrated Knowledge Graph to Automate Cloud Data Compliance
用于自动化云数据合规性的集成知识图
DOI:
10.1109/access.2020.3008964
发表时间:
2020
期刊:
IEEE Access
影响因子:
3.9
作者:
[Joshi, Karuna Pande, Elluri, Lavanya, Nagar, Ankur]
通讯作者:
Nagar, Ankur
A Semantic Approach for Automating Knowledge in Policies of Cyber Insurance Services
网络保险服务政策知识自动化的语义方法
DOI:
10.1109/icws.2019.00018
发表时间:
2019
期刊:
2019 IEEE International Conference on Web Services (ICWS
影响因子:
--
作者:
[Joshi, Ketki, Pande Joshi, Karuna, Mittal, Sudip]
通讯作者:
Mittal, Sudip
IUCRC Phase II UMBC: Center for Accelerated Real time Analytics (CARTA)
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批准号:2310844
-
项目类别:Continuing Grant
-
资助金额:$50.0万
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财政年份:2023
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负责人:Karuna Joshi
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依托单位:
海外基金