Analysis of Performance-impacting Factors on Checkpointing Frameworks: The CPPC Case Study

2011 ◽  
Vol 54 (11) ◽  
pp. 1821-1837 ◽  
Author(s):  
G. Rodriguez ◽  
M. J. Martin ◽  
P. Gonzalez ◽  
J. Tourino
Keyword(s):  
Impacting Factors ◽  
Analysis Of Performance

scholarly journals GENDER AND PERFORMANCE IN ARABIC LANGUAGE LEARNING IN LAGOS

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Tijani Akinola MOGAJI
Keyword(s):  
Language Learning ◽  
Sampling Technique ◽  
Arabic Language ◽  
Female Students ◽  
Survey Method ◽  
Gender Analysis ◽  
And Performance ◽  
Analysis Of Performance ◽  
Better Than

This study focused on gender analysis of performance and enrolment for Arabic Language in a selected Arabic school in Lagos State. The study adopted the survey method for choosing the admitted students during the three years between 2014 and 2016. The purposive sampling technique was employed to select Daaru Da’wah wal Irshaad as a case study. The results revealed that the male Arabic students performed significantly better than the female students. Secondly, it indicated that the enrolment of males is far higher than that of females. The study concludes on the need to encourage the womenfolk to cultivate Arabic learning and sensitize them on the wealth of opportunity accruable from learning the language. Keywords: Arabic language, gender, enrolment, performance, Arabic schools

scholarly journals Impacting Factors, Dynamic Process, and Correction of Adsorption Reduction in Shale Reservoir: A Case Study on Shale Samples from the Western Guizhou

ACS Omega ◽  
2020 ◽  
Vol 5 (24) ◽  
pp. 14597-14610
Author(s):  
Guanwen Lu ◽  
Chongtao Wei ◽  
Jilin Wang ◽  
Ruiyan Meng ◽  
Landry Soh Tamehe
Keyword(s):  
Dynamic Process ◽  
Impacting Factors ◽  
Adsorption Reduction ◽  
Shale Reservoir ◽  
Western Guizhou

Performance analysis of Mobile Cloud Computing Architectures for mHealth app

2020 ◽  
Vol 2020 (3) ◽  
pp. 335-1-335-7
Author(s):  
D. Inupakutika ◽  
D. Akopian ◽  
P. Chalela ◽  
A. G. Ramirez
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Mobile User ◽  
Battery Life ◽  
Mobile Cloud ◽  
Medical Monitoring ◽  
Power And Energy ◽  
Analysis Of Performance

Mobile Health (mHealth) applications (apps) are being widely used to monitor health of patients with chronic medical conditions with the proliferation and the increasing use of smartphones. Mobile devices have limited computation power and energy supply which may lead to either delayed alarms, shorter battery life or excessive memory usage limiting their ability to execute resource-intensive functionality and inhibit proper medical monitoring. These limitations can be overcome by the integration of mobile and cloud computing (Mobile Cloud Computing (MCC)) that expands mobile devices' capabilities. With the advent of different MCC architectures such as implementation of mobile user-side tools or network-side architectures it is hence important to decide a suitable architecture for mHealth apps. We survey MCC architectures and present a comparative analysis of performance against a resource demanding representative testing scenario in a prototype mHealth app. This work will compare numerically the mobile cloud architectures for a case study mHealth app for Endocrine Hormonal Therapy (EHT) adherence. Experimental results are reported and conclusions are drawn concerning the design of the prototype mHealth app system using the MCC architectures.

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