This paper presents a review of user expectation towards Augmented Reality (AR) and the acceptance of AR for technologyenhanced teaching and learning. Augmented Reality is a technology that superimposes a computer-generated image over a user's view of the real world, thus providing a composite view. This technology has been used in many fields such as marketing, military, entertainment and many other sectors. Studies have found that AR technology can enhance teaching and learning, however more research still needs to be conducted about the acceptance of AR as a learning tool and what users in education expect from the technology. An understanding of the user expectation is one of the key foundations towards establishing better-designed AR systems and applications that will result in more acceptance of this technology. To help with this, this paper reviews previous research on user expectations of AR in education and its acceptance.

No abstract

<p>Technological development is a revolutionary process by this time, it is<br />mainly depending on electronic applications in our daily routines like<br />(business management, banking, financial transfers, health, and other essential<br />traits of life). Identification or approving identity is one of the complicated<br />issues within online electronic applications. Person’s writing style can be<br />employed as an identifying biological characteristic in order to recognize the<br />identity. This paper presents a new way for identifying a person in a social<br />media group using comments and based on the Deep Neural Network. The<br />text samples are short text comments collected from Telegram group in Arabic<br />language (Iraqi dialect). The proposed model is able to extract the person's<br />writing style features in group comments based on pre-saved dataset. The<br />analysis of this information and features forms the identification decision.<br />This model exhibits a range of prolific and favorable results, the accuracy that<br />comes with the proposed system reach to 92.88% (+/- 0.16%).</p>

No abstract

No abstract