A commercial, benefit driven and secure framework for elearning in cloud computing

Sandhu, Rajinder; Sood, Sandeep K.

doi:10.1002/cae.21621

Cited by 8 publications

(5 citation statements)

References 29 publications

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“…Singh et al (2018) proposed a model based on Fog computing and IoT that classifies dengue patients into different categories like infected, severely infected, and safe based on their symptoms. Sandhu and Sood (2015) presented an e‐learning system based on cloud computing and the Design Science Research method. Sandhu et al (2018) proposed a framework related to data mining that has an efficient method for storing information granules.…”

Section: Related Workmentioning

confidence: 99%

Fog‐assisted virtual reality‐based learning framework to control panic

Sood

Rawat

2021

Expert Systems

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The biggest challenges for several universities and educational institutions throughout the COVID‐19 pandemic are online and e‐learning infrastructure availability. The incorporation of Information and Communication Technologies in the domain of disaster management is one such dimension, which focuses on the sustainability of human beings regarding the handling of unexpected pandemics. Therefore, it is important to evaluate the panic well‐being of the student in this situation. Moreover, virtual reality technology provides a virtual classroom environment that improves the skill and knowledge of the students at remote sites. In this paper, a fog‐assisted cyber physical system is proposed that deals with the various aspects of the panic well‐being of the student, including the virtual reality platform for remote learning. The proposed system utilizes the concepts of physical and cyberspace. The physical space facilitates real‐time data acquisition, and cyberspace determines and predicts the panic well‐being of the student. The performance assessment of the proposed model acknowledges the efficiency of the virtual learning system and panic well‐being determination and prediction. The proposed system also discussed a virtual learning system that provides a virtual classroom environment to the students at remote sites and reduces the panic due to stressful times during the COVID‐19 pandemic.

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Section: Related Workmentioning

confidence: 99%

Fog‐assisted virtual reality‐based learning framework to control panic

Sood

Rawat

2021

Expert Systems

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“…Peer assessment is used as a formative procedure that enhances the learning of students with the opportunity to peer assess with each other's work. Sandhu and Sood proposed a layered structure consisting of five layers each dedicated to a specific task. This cloud‐based commercial and benefit‐driven e‐learning system fulfills the need of multiple education service providers and end users separately.…”

Section: State‐of‐the‐artmentioning

confidence: 99%

Optical fog‐assisted smart learning framework to enhance students’ employability in engineering education

Sood

Singh

2019

Comp Applic In Engineering

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In the present scenario, the state of engineering education worldwide is facing a big challenge of the employability of graduates. Cloud computing technology has changed the educational landscape by allowing educators and administrators to shift to the cloud for making actionable decisions. In this paper, a smart learning framework is proposed where universities/colleges can advocate the management of employability enhancement and start skill-set enhancement courses through e-learning. This proposed framework monitors the academic/skill data of students to classify their employability at the early stage of graduation. In addition, an algorithm is proposed for skill-set assessment to find various clusters of students who lack in required skill-set. The predicted clusters of students can be offered opportunities to improve their required skill-set through e-learning. Further, we used the design science research methodology for conducting online courses. Moreover, the prediction of resource usage of the proposed e-learning framework is calculated to improve its effectiveness. In our experiment, results show that our proposed hybrid classier achieves 96.45% accuracy of classification. The prediction of resource usage offers better opportunities for adaptive resource elasticity. The results depict that by introducing the proposed framework in engineering education; more effective decisions can be made to improve the employability and overall growth of students. K E Y W O R D S employability enhancement, fog/cloud computing, optical network, resource usage pattern prediction, skill-set assessment, smart learning 1 | INTRODUCTION Universities/colleges are under great pressure to make the youth ready for jobs since the market demands for skilled workers. The education system throughout the world requires a smart system that can be monitored, controlled, quantitatively measured, and continuously improved with the collaboration of universities/ learning centers to enhance students' employability potential during their early years of graduation. Students' employability depends on a variety of features, such as marks obtained in high school, diploma, graduation, etc., extra technical competence, or other relevant information [29]. The information collected from various resources regarding their features is to be accurate, well-timed and precise.As it may be seen in the next references along with this article, according to authors [1,3,4,10,35,37,38,40,41], today's technology is capable of improving students' skills towards employability through e-learning. It consists of multiple skill-set service providers such as learning centers, recruitment companies, institutions, and private training centers, etc. It provides a personally customized and effective educational environment that reduces the gap between students' skill-set and industry demand at multiple employability parameters, such as aptitude, reasoning, communication, technical/professional certifications, etc.The potential of cloud computing encourages education syste...

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“…Management of the collected data requires a scalable and distributed network infrastructure that meets high standards , such as cloud infrastructure. Since the big data and cloud computing are rapidly growing areas in the healthcare domain , these technologies need to be included in university smart healthcare courses . For instance, the curriculum of data science course at Indiana University and cloud computing course at the University of Texas at San Antonio incorporate fundamental aspects of big data and cloud computing, respectively and provide training for students in various technological areas .…”

Section: Background and Motivationmentioning

confidence: 99%

Designing a course for smart healthcare engineering education

Rodić-Trmčić

Лабус

Barać

et al. 2017

Comp Applic In Engineering

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Smart healthcare is an emerging concept that relies on the synergy of various engineering concepts and intelligent technical innovations applicable to healthcare. Demand for smart healthcare engineers is anticipated to grow, hence, arising a need to educate profile engineers. The goal of this paper is to introduce an approach to designing a course for smart healthcare engineering education. Through the key topics of the course, students acquired new skills and knowledge from emerging technologies underlying smart healthcare. The proposed approach was evaluated at a graduate course at the Faculty of Organizational Sciences, University of Belgrade. The results indicate that there was a positive impact on the learning process as well as a positive learning experience.

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A commercial, benefit driven and secure framework for elearning in cloud computing

Cited by 8 publications

References 29 publications

Fog‐assisted virtual reality‐based learning framework to control panic

Fog‐assisted virtual reality‐based learning framework to control panic

Optical fog‐assisted smart learning framework to enhance students’ employability in engineering education

Designing a course for smart healthcare engineering education

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