Unveiling the Depths of Comprehension in E-Reading and Paper Reading: A Systematic Literature Review

Anees Albasri, Sina Alizadeh Tabrizi — Sun, 08 Sep 2024 00:00:00 +0000

It is deemed that human brain is highly flexible which provides the ground for learning so many new things, while it is also the case that when it comes to reading from different mediums, that flexibility can be a problem. That is, the brain mechanism during paper reading and e-reading is significantly different. There are numerous studies from cognitive sciences, neuroscience, education, etc. which have studied the topic from various perspectives, while there is a lack of literature which systematically reviewed the primary studies to gain insight into comprehension change across media platforms, a comparison between e-reading and paper reading in terms of comprehension and whether e-reading substitutes paper reading. In the present paper, the main objective is the comparison between e-reading and paper reading in terms of comprehension. For this purpose, systematic literature review method was adopted and three major indexes, namely, Scopus, WoS and IEEE Xplore were selected as the source of corpus. Totally, 27 papers were found, after applying inclusion and exclusion criteria the number of the papers was decreased. The results showed that there are several factors effective on reading comprehension, such as Story elements, Characters analysis, Main idea and details, Problems and solution Eyestrain, Headaches, Distraction, Mentally mapping, Availability, Portability, Eco- friendly, Font size, Tools, Reading program, Convenience, Compatibility, Media richness, Licensing issues, Graphic display capabilities, Reading task and Reading techniques Eye strain, Time constraint Gender, Age, Pleasure, Motivation, Challenge, Involvement, Curiosity, Competition, Recognition, Social aspects, Compliance, Grades, Personal relationship, Readership, Reading experience, Context area of school, Context constraints, Reader comfort and Mental values. Moreover, while some studies point out that there is no significant difference between comprehension of reading across media, other studies showed that there are differences among study subjects in terms of comprehension, if age, gender, experience, etc. are taken into account.

Traversing Dynamic Environments: Advanced Deep Reinforcement Learning for Mobile Robots Path Planning - A Comprehensive Review

maysam qasm, Salah Al-Darraji — Sat, 14 Sep 2024 00:00:00 +0000

Enabling mobile robots to navigate unpredictable and ever-changing environments while avoiding static and moving obstacles is a critical challenge for dynamic path planning. Advanced sensors have simplified the robot’s work by enabling it to navigate autonomously without human intervention. Optimal path planning in dynamic environments requires sophisticated algorithms considering essential factors such as time, energy, and distance. These problems can be solved using deep neural networks (DNNs) and reinforcement learning (RL). An artificial intelligence (AI) agent learns from reward signals using trial and error to identify humans' optimal behavioral strategies. This review paper explores how deep reinforcement learning (DRL) techniques can be combined with other path-planning techniques to enhance the efficiency of these methods and solutions to address the problem of efficient navigation in unfamiliar environments with obstacles, with a focus on processes such as policy gradient, model-free and model-based learning, and the actor-critic approach. We comprehensively examine the key concepts, challenges, and recent developments in DRL, focusing on its application to revolutionize robotic navigation in complex scenarios.

Iraqi Journal of Intelligent Computing and Informatics (IJICI)

Unveiling the Depths of Comprehension in E-Reading and Paper Reading: A Systematic Literature Review

Traversing Dynamic Environments: Advanced Deep Reinforcement Learning for Mobile Robots Path Planning - A Comprehensive Review