All Stories

  1. Reconnaissance attack detection via boosting machine learning classifiers
  2. A Conceptual Framework for Determining Quality Requirements for Mobile Learning Applications Using Delphi Method
  3. Propose a New Quality Model for M-Learning Application in Light of COVID-19
  4. A Novel Hybrid Trustworthy Decentralized Authentication and Data Preservation Model for Digital Healthcare IoT Based CPS
  5. Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs
  6. An Industrial IoT-Based Blockchain-Enabled Secure Searchable Encryption Approach for Healthcare Systems Using Neural Network
  7. Factors Affecting Students’ Acceptance of Mobile Learning Application in Higher Education during COVID-19 Using ANN-SEM Modelling Technique
  8. Examining the Factors Influencing the Mobile Learning Applications Usage in Higher Education during the COVID-19 Pandemic
  9. A Conceptual Model to Investigate the Role of Mobile Game Applications in Education during the COVID-19 Pandemic
  10. Sustainable Applications of Smart-Government Services: A Model to Understand Smart-Government Adoption
  11. For Sustainable Application of Mobile Learning: An Extended UTAUT Model to Examine the Effect of Technical Factors on the Usage of Mobile Devices as a Learning Tool
  12. Social Media Applications Affecting Students’ Academic Performance: A Model Developed for Sustainability in Higher Education
  13. Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic
  14. An Anonymous Channel Categorization Scheme of Edge Nodes to Detect Jamming Attacks in Wireless Sensor Networks
  15. Mobile Government Adoption Model Based on Combining GAM and UTAUT to Explain Factors According to Adoption of Mobile Government Services
  16. Multilayer Neural Network based on MIMO and Channel Estimation for Impulsive Noise Environment in Mobile Wireless Networks
  17. Thematic Analysis for Classifying the Main Challenges and Factors Influencing the Successful Implementation of E-learning System Using NVivo
  18. Investigating the main determinants of mobile cloud computing adoption in university campus
  19. Factors Influencing the Adoption of E-government Services among Jordanian Citizens
  20. Analysis the Effect of Different Factors on the Development of Mobile Learning Applications at different stages of usage
  21. An Efficient Load Balancing Scheme of Energy Gauge Nodes to Maximize the Lifespan of Constraint Oriented Networks
  22. Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor Networks
  23. The Role of Compatibility and Task-Technology Fit (TTF): On Social Networking Applications (SNAs) Usage as Sustainability in Higher Education
  24. An Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks to Maximize Their Lifespan in an Operational Environment
  25. Improved Security Particle Swarm Optimization (PSO) Algorithm to Detect Radio Jamming Attacks in Mobile Networks
  26. MAC-AODV Based Mutual Authentication Scheme for Constraint Oriented Networks
  27. Crowd-reflecting: a counterproductive experience of Arab adult learning via technology
  28. Towards a Model of Quality Features for Mobile Social Networks Apps in Learning Environments: An Extended Information System Success Model
  29. Analysis of the Effect of Course Design, Course Content Support, Course Assessment and Instructor Characteristics on the Actual Use of E-learning System
  30. Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education
  31. Analysis of the essential factors affecting of intention to use of mobile learning applications: A comparison between universities adopters and non-adopters
  32. Examination of factors influencing the use of mobile learning system: An empirical study
  33. Malay Language Mobile Learning System (MLMLS) using NFC Technology
  34. Acceptance and usage of a mobile information system services in University of Jordan
  35. Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives
  36. Extending the TAM to examine the effects of quality features on mobile learning acceptance
  37. Investigating Students' Perceptions on Mobile Learning Services