Proceedings. IEEE International Conference on Big Data Computing Service and Applications最新文献

筛选
英文 中文
Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure. 在基于网络的基础设施中评估质谱大数据分布式查询和搜索的模拟试验台。
Proceedings. IEEE International Conference on Big Data Computing Service and Applications Pub Date : 2021-08-01 Epub Date: 2021-10-18 DOI: 10.1109/bigdataservice52369.2021.00022
Umair Mohammad, Fahad Saeed
{"title":"Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure.","authors":"Umair Mohammad,&nbsp;Fahad Saeed","doi":"10.1109/bigdataservice52369.2021.00022","DOIUrl":"10.1109/bigdataservice52369.2021.00022","url":null,"abstract":"<p><p>Advance access and reuse mechanisms for large-scale Mass Spectrometry (MS) data are essential for democratizing data for the omics research community and making it adhere to FAIR (Findable, Accessible, Interoperable, Reusable) principles. Although a number of centralized data repositories have been established, they have been limited to search mechanisms that depend on the meta-data associated with these MS datasets. Furthermore, they require constant influx of resources for maintenance. In this paper, we proposed an alternative novel distributed infrastructure for direct MS/MS spectral search. We designed and developed a simulation testbed using concepts from computer networks, queuing theory, and stochastic simulation methods. Results show that a distributed MS search based on raw MS/MS spectra can scale gracefully for up-to 2000 participating nodes, while simultaneously processing queries using the proposed networked infrastructure on the order of milliseconds to a few seconds for up-to a total of fifty billion MS/MS spectra.</p>","PeriodicalId":93613,"journal":{"name":"Proceedings. IEEE International Conference on Big Data Computing Service and Applications","volume":"2021 ","pages":"137-142"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007159/pdf/nihms-1794436.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49686121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The 5I Model of Smart City: A Case of Shanghai, china 智慧城市的5I模式——以上海为例
Proceedings. IEEE International Conference on Big Data Computing Service and Applications Pub Date : 2015-03-30 DOI: 10.1109/BigDataService.2015.34
Xixi Lin, H. Quan, Hong Zhang, Yinghua Huang
{"title":"The 5I Model of Smart City: A Case of Shanghai, china","authors":"Xixi Lin, H. Quan, Hong Zhang, Yinghua Huang","doi":"10.1109/BigDataService.2015.34","DOIUrl":"https://doi.org/10.1109/BigDataService.2015.34","url":null,"abstract":"Smart City has become the new developing target of modern city. Analyzing in depth the characteristics and connotation of Smart City and listing analysis dimensions for Smart City construction have the vital practical significance. This paper builds the 5I model of Smart City from four perspectives of information infrastructure construction, information perception and intelligent application, new generation of information technology industry and information security assurance. To have a more clear exposition of the present situation of Smart City construction from 5I model, this paper takes Shanghai for example to provide rational analysis perspectives and scientific references for the development of Smart City all over the world.","PeriodicalId":93613,"journal":{"name":"Proceedings. IEEE International Conference on Big Data Computing Service and Applications","volume":"41 1","pages":"329-332"},"PeriodicalIF":0.0,"publicationDate":"2015-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90497914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
MOOC for Medical Big Data Research: An Important Role in Hypertension Big Data Research 医学大数据研究MOOC:在高血压大数据研究中的重要作用
Proceedings. IEEE International Conference on Big Data Computing Service and Applications Pub Date : 2015-03-30 DOI: 10.1109/BIGDATASERVICE.2015.37
Xinyan Wang, L. Tian, Bo Xu, Xueliang Wang, Wenjun Wu
{"title":"MOOC for Medical Big Data Research: An Important Role in Hypertension Big Data Research","authors":"Xinyan Wang, L. Tian, Bo Xu, Xueliang Wang, Wenjun Wu","doi":"10.1109/BIGDATASERVICE.2015.37","DOIUrl":"https://doi.org/10.1109/BIGDATASERVICE.2015.37","url":null,"abstract":"Due to limited technical and social resources, many physician practices fall short on accurate blood pressure measurement to carry out large-scale hypertension research projects. The accuracy and standard of data acquisition are very important when data sources are diverse in medical big data research. This paper proposes Massive Online Open Course (MOOC) is appropriate approach to teach volunteers necessary knowledge and skills of blood pressure measurement for hypertension research. It introduces a new citizen science \"paradigm\" to support big data research such as hypertension. MOOC is a new type online course that provides a combination of short video lectures, frequent comprehension quizzes and active participation in discussion forum. The well-trained data collectors by MOOC will be granted to collect and publish data of hypertension research. The process of medical big data research based on MOOC was introduced.","PeriodicalId":93613,"journal":{"name":"Proceedings. IEEE International Conference on Big Data Computing Service and Applications","volume":"124 1","pages":"453-455"},"PeriodicalIF":0.0,"publicationDate":"2015-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77335966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Bankruptcy Prediction of Construction Businesses: Towards a Big Data Analytics Approach 建筑企业破产预测:走向大数据分析方法
Proceedings. IEEE International Conference on Big Data Computing Service and Applications Pub Date : 2015-01-01 DOI: 10.1109/BigDataService.2015.30
H. Alaka, Lukumon O. Oyedele, M. Bilal, Olúgbénga O. Akinadé, H. Owolabi, Saheed Ajayi
{"title":"Bankruptcy Prediction of Construction Businesses: Towards a Big Data Analytics Approach","authors":"H. Alaka, Lukumon O. Oyedele, M. Bilal, Olúgbénga O. Akinadé, H. Owolabi, Saheed Ajayi","doi":"10.1109/BigDataService.2015.30","DOIUrl":"https://doi.org/10.1109/BigDataService.2015.30","url":null,"abstract":"","PeriodicalId":93613,"journal":{"name":"Proceedings. IEEE International Conference on Big Data Computing Service and Applications","volume":"251 1","pages":"347-352"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75757591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信