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Dr. Mohammed Khaleel
King Khalid University, Abha, saudi Arabia

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0 E Learning
0 Mobile Cloud Computing
0 Medical Data Mining
0 Data Science
0 Data science and AI in healthcare

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Journal article
Published: 02 March 2021 in Sustainability
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E-Learning has proven to be the only resort as a replacement of traditional face-to-face learning methods in the current global lockdown due to COVID-19 pandemic. Academic institutions across the globe have invested heavily into E-Learning and the majority of the courses offered in traditional classroom mode have been converted into E-Learning mode. The success of E-Learning initiatives needs to be ensured to make it a sustainable mode of learning. The objective of the current study is to propose a holistic E-Learning service framework to ensure effective delivery and use of E-Learning Services that contributes to sustainable learning and academic performance. Based on an extensive literature review, a proposed theoretical model has been developed and tested empirically. The model identifies a broad range of success determinants and relates them to different success measures, including learning and academic performance. The proposed model was validated with the response from 397 respondents involved with an E-Learning system in the top five public universities in the southern region of Saudi Arabia through the Partial Least Squares regression technique using SmartPLS software. Five main factors (Learner’s Quality, Instructor’s Quality, Information’s Quality, System’s Quality and Institutional Quality) were identified as a determinant of E-Learning service performance which together explains 48.7% of the variance of perceived usefulness of ELS, 71.2% of the variance of use of the E-Learning system. Perceived usefulness of ELS and use of ELS together explain 70.6% of learning and academic performance of students. Hence the framework will help achieve the sustainable and successful adoption of E-Learning services.

ACS Style

Mohammad Alam; Naim Ahmad; Quadri Naveed; Ayyub Patel; Mohammed Abohashrh; Mohammed Khaleel. E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study. Sustainability 2021, 13, 2653 .

AMA Style

Mohammad Alam, Naim Ahmad, Quadri Naveed, Ayyub Patel, Mohammed Abohashrh, Mohammed Khaleel. E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study. Sustainability. 2021; 13 (5):2653.

Chicago/Turabian Style

Mohammad Alam; Naim Ahmad; Quadri Naveed; Ayyub Patel; Mohammed Abohashrh; Mohammed Khaleel. 2021. "E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study." Sustainability 13, no. 5: 2653.

Review
Published: 07 November 2019 in Applied Sciences
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Estimation of fault classification and location in a multi-terminal high voltage direct current (MT–HVdc) transmission system is a challenging problem and is considered to be a fundamental maneuver of dc grid protection. This research paper critically reviews traveling and non-travelling wave methods of classification and location of dc faults in multi-terminal HVdc transmission systems. Detailed mathematical analysis of MT–HVdc systems composed of high grounding resistance, cable and overhead line segments, and bipolar coupled transmission network under healthy and faulty conditions, are evaluated. The gravity of this research paper addresses benefits and shortcomings of traveling and non-traveling wave methods and futuristic techniques of fault classification and location.

ACS Style

Raheel Muzzammel; Ali Raza; Mohammad Rashid Hussain; Ghulam Abbas; Ishtiaq Ahmed; Mohammed Qayyum; Mohammad Ashiquee Rasool; Mohammed Abdul Khaleel. MT–HVdc Systems Fault Classification and Location Methods Based on Traveling and Non-Traveling Waves—A Comprehensive Review. Applied Sciences 2019, 9, 4760 .

AMA Style

Raheel Muzzammel, Ali Raza, Mohammad Rashid Hussain, Ghulam Abbas, Ishtiaq Ahmed, Mohammed Qayyum, Mohammad Ashiquee Rasool, Mohammed Abdul Khaleel. MT–HVdc Systems Fault Classification and Location Methods Based on Traveling and Non-Traveling Waves—A Comprehensive Review. Applied Sciences. 2019; 9 (22):4760.

Chicago/Turabian Style

Raheel Muzzammel; Ali Raza; Mohammad Rashid Hussain; Ghulam Abbas; Ishtiaq Ahmed; Mohammed Qayyum; Mohammad Ashiquee Rasool; Mohammed Abdul Khaleel. 2019. "MT–HVdc Systems Fault Classification and Location Methods Based on Traveling and Non-Traveling Waves—A Comprehensive Review." Applied Sciences 9, no. 22: 4760.