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Joint DNN partitioning and task offloading in mobile edge computing via deep reinforcement learning
As Artificial Intelligence (AI) becomes increasingly prevalent, Deep Neural Networks (DNNs) have become a crucial tool for develo** and advancing...
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Teaching methodology for people with intellectual disabilities: a case study in learning ballet with mobile devices
Develo** artistic skills in students with intellectual disabilities (ID) entails several difficulties including selecting the appropriate teaching...
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A mobile learning framework for higher education in resource constrained environments
It is well documented that learning oppourtunities afforded by mobile technology (m-learning) holds great potential to enhance technology-enhanced...
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Mobile English Learning: A Meta-analysis
The advantages of mobile learning (m-learning) in English education have been widely described in previous research; however, there is little...
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Characteristic features of modern teaching music methods in East Asia: Examining the influence of interactive learning and mobile apps on musical self-esteem
The introduction of modern vocal teaching techniques will promote the change in the music curricula in East Asia. The study explores the impact of...
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Employing Mobile Learning in Music Education
This study sought to evaluate the effectiveness of introducing digital software in music education to improve academic performance and solfeggio...
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CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile
Leaf and fruit infections are the primary cause of the maximum harm to the crop, which decreases the quality and amount of the goods. To improve the...
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Factors affecting university students switching intention to mobile learning: a push-pull-mooring theory perspective
Adopting technology by its intended users is one of the most important contributors to that technology’s success. Therefore, the success of mobile...
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Just-in-time defect prediction for mobile applications: using shallow or deep learning?
Just-in-time defect prediction (JITDP) research is increasingly focused on program changes instead of complete program modules within the context of...
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Impact of Mobile Technology on Learning and Library Policies
This paper presents interim results of a study conducted in 2021 and being currently continued. The study aims to analyse the up-to-date demands of...
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Learning the micro-environment from rich trajectories in the context of mobile crowd sensing
With the rapid advancements of sensor technologies and mobile computing, Mobile Crowd Sensing (MCS) has emerged as a new paradigm to collect...
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Mobile learning: Pre-service teachers’ perceptions of integrating iPads into future teaching
This study investigated pre-service teachers’ perceptions of using iPads in teaching, with a focus on motivation to adopt iPads, iPad-integration...
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Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions
Due to the outbreak of COVID 19, digital learning has become the most efficient learning and teaching technique adopted across the world. The...
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Architectural Support for Context-Aware Mobile Learning Applications
Context-aware mobile learning applications provide learning materials to suit the needs of individual learners. Despite several applications...
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Minimize average tasks processing time in satellite mobile edge computing systems via a deep reinforcement learning method
Recently, the development of Low Earth Orbit (LEO) satellites and the advancement of the Mobile Edge Computing (MEC) paradigm have driven the...
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Using Mobile gamified quizzing for active learning: the effect of reflective class feedback on undergraduates’ achievement
This study investigated whether reflective class feedback (RCF) boosts the effectiveness of mobile gamified quizzing in enhancing active learning in...
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Plant disease detection using deep learning based Mobile application
Crop disease serves as a major threat to the farming sector. Due to the increased utilization of smartphones, it is now possible to leverage the...
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Deep reinforcement learning-based microservice selection in mobile edge computing
In mobile edge computing environment, due to resources constraints of edge devices, when user locations continue changing, the network will be...
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Mobile-assisted language learning in Chinese higher education context: a systematic review from the perspective of the situated learning theory
Recent years have witnessed numerous systematic investigations on mobile-assisted language learning (MALL). However, very few research synthesis...
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Deep recurrent Q-learning for energy-constrained coverage with a mobile robot
In this paper, we study the problem of coverage of an environment with an energy-constrained robot in the presence of multiple charging stations. As...
