درخت حوزه‌های تخصصی

The purpose of this research is to explore the social media trend in communication in Kuwait by utilizing the technology acceptance model. Social media has been gaining extraordinary adoption in past years that requires further investigation into user’s adoption habits, the various kinds of social media, and its effect on their perceived usefulness and ease of use of social media. The study consists of a total of 250 participants that were asked to complete a questionnaire in a random sample. Important findings indicate that the highest number of participants uses Facebook, and the second highest number of participants use Twitter. In terms of usage habits, the highest number of participants uses social media for chatting and connecting with family and friends. The second highest number of participants uses social media for reading posts. In terms of perceived usefulness, the highest numbers of participants perceive social media as ‘usefulness’, and the second highest numbers of participants feel that ‘social media is faster’. In terms of perceived ease of use the highest numbers of participants feel that social media is an easy way to communicate, and the second highest numbers of participants feel that social media does not require a lot of effort. In terms of gender it has been evident that females feel higher perceived usefulness and perceived ease of use of social media than males. The study bears theoretical and practical implications that show TAM can be successfully applied to examine social media in the context of Kuwait population. Furthermore, results of this study can be further generalized to neighboring GCC countries as they share similar geographic, economic, cultural, and financial factors.

Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips and games. Here's the show the congestion problem arises and represent   aim of the research is to avoid congestion at APs to wireless networks by adding a control before congestion occurs. A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. The results show that if the amount of information in the input data is large, a more accurate prediction can be made.