Analysis of the Cloud Computing Paradigm on Mobile Health Records Systems

2012 ◽  
Author(s):  
Gonzalo Fern'ndez ◽  
Isabel de la Torre-Diez ◽  
Joel J.P.C. Rodrigues
Keyword(s):  
Cloud Computing ◽  
Mobile Health ◽  
Health Records ◽  
Computing Paradigm

Protecting Mobile Health Records in Cloud Computing

2017 ◽  
Vol 16 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Jianghua Liu ◽  
Jinhua Ma ◽  
Wei Wu ◽  
Xiaofeng Chen ◽  
Xinyi Huang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Health ◽  
Health Records

Feature

2010 ◽  
Vol 14 (05n06) ◽  
pp. 22-38
Keyword(s):  
Cancer Patients ◽  
Biodiversity Conservation ◽  
Mobile Health ◽  
Health Records ◽  
Drug Companies ◽  
A Priority ◽  
Vein Harvesting

Biodiversity Conservation is Everyone's Business. Search for ASEAN Champions of Biodiversity is On. Drug Companies Reduce Prices of Medicines. SWS: Make Health A Priority, Filipinos Ask Next Leaders. New Vein Harvesting Technology. Mobile Health Records in Malaysia. Faster, Accurately Targeted Radiation Cancer Patients. SingHealth Selects IBM and SAP To Transform HR Processes.

scholarly journals Extending the usage of graphics processing units on the cloud for cost savings on seismic data regularization

2021 ◽  
Vol 38 (2) ◽  
Author(s):  
Nicholas Torres Okita ◽  
Tiago A. Coimbra ◽  
José Ribeiro ◽  
Martin Tygel
Keyword(s):  
Cloud Computing ◽  
Graphics Processing Units ◽  
Cost Savings ◽  
Data Sets ◽  
Computing Paradigm ◽  
Common Reflection Surface ◽  
User Demand ◽  
Computationally Intensive ◽  
Zero Offset ◽  
Graphics Processing

ABSTRACT. The usage of graphics processing units is already known as an alternative to traditional multi-core CPU processing, offering faster performance in the order of dozens of times in parallel tasks. Another new computing paradigm is cloud computing usage as a replacement to traditional in-house clusters, enabling seemingly unlimited computation power, no maintenance costs, and cutting-edge technology, dynamically on user demand. Previously those two tools were used to accelerate the estimation of Common Reflection Surface (CRS) traveltime parameters, both in zero-offset and finite-offset domain, delivering very satisfactory results with large time savings from GPU devices alongside cost savings on the cloud. This work extends those results by using GPUs on the cloud to accelerate the Offset Continuation Trajectory (OCT) traveltime parameter estimation. The results have shown that the time and cost savings from GPU devices’ usage are even larger than those seen in the CRS results, being up to fifty times faster and sixty times cheaper. This analysis reaffirms that it is possible to save both time and money when using GPU devices on the cloud and concludes that the larger the data sets are and the more computationally intensive the traveltime operators are, we can see larger improvements.Keywords: cloud computing, GPU, seismic processing. Estendendo o uso de placas gráficas na nuvem para economias em regularização de dados sísmicosRESUMO. O uso de aceleradores gráficos para processamento já é uma alternativa conhecida ao uso de CPUs multi-cores, oferecendo um desempenho na ordem de dezenas de vezes mais rápido em tarefas paralelas. Outro novo paradigma de computação é o uso da nuvem computacional como substituta para os tradicionais clusters internos, possibilitando o uso de um poder computacional aparentemente infinito sem custo de manutenção e com tecnologia de ponta, dinamicamente sob demanda de usuário. Anteriormente essas duas ferramentas foram utilizadas para acelerar a estimação de parâmetros do tempo de trânsito de Common Reflection Surface (CRS), tanto em zero-offset quanto em offsets finitos, obtendo resultados satisfatórios com amplas economias tanto de tempo quanto de dinheiro na nuvem. Este trabalho estende os resultados obtidos anteriormente, desta vez utilizando GPUs na nuvem para acelerar a estimação de parâmetros do tempo de trânsito em Offset Continuation Trajectory (OCT). Os resultados obtidos mostraram que as economias de tempo e dinheiro foram ainda maiores do que aquelas obtidas no CRS, sendo até cinquenta vezes mais rápido e sessenta vezes mais barato. Esta análise reafirma que é possível economizar tanto tempo quanto dinheiro usando GPUs na nuvem, e conclui que quanto maior for o dado e quanto mais computacionalmente intenso for o operador, maiores serão os ganhos de desempenho observados e economias.Palavras-chave: computação em nuvem, GPU, processamento sísmico. 

scholarly journals A Support Framework for the Migration of E-Government Services to the Cloud

2016 ◽  
pp. 124-162
Author(s):  
Abílio Cardoso ◽  
Fernando Moreira ◽  
Paulo Simões
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Service Management ◽  
Federal Agencies ◽  
Technology Infrastructure ◽  
Information Technology Infrastructure ◽  
Government Services ◽  
Computing Paradigm ◽  
Technology Service ◽  
Information Technology Service

Public and federal agencies from countries around the world are increasingly providing information technology based services via the Internet - known as e-government. Several of the general requirements of e-government services are satisfactorily met by the emerging Cloud Computing paradigm that promises a number of benefits such as service elasticity (the ability to handle peaks and troughs of demands); optimization of costs; capacity to handle large volumes of data; and a generalized model of Internet-based access for end-users. For this reason, it is no surprise that Cloud related technologies are gradually leveraging e-government platforms. In this chapter, a support framework is outlined that complies with and extends the well-known ITIL (Information Technology Infrastructure Library) set of best practices for IT (Information Technology) service management. It is suggested that the proposed framework can be usefully deployed to assist in the process of migrating e-government services provision to the Cloud Computing environment.

An efficient privacy solution for electronic health records in cloud computing

2020 ◽  
Vol 9 (4) ◽  
pp. 201
Author(s):  
Abdelkarim Ait Temghart ◽  
Feda AlShahwan ◽  
Mbarek Marwan ◽  
Fatima Sifou
Keyword(s):  
Cloud Computing ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health
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