Abstract:

In this research study, we investigate the effectiveness of a proposed automated framework that leverages AI algorithms to improve the accuracy, scalability, and efficiency of data analysis. We compare the performance of the proposed framework to traditional data analysis methods in terms of accuracy, time and effort required for data analysis, and scalability. We conducted a questionnaire-based survey to collect data on the application of the proposed framework and traditional data analysis methods in real-world scenarios. We used statistical analyses, including t-tests and regression analyses, to analyze the data and draw conclusions. Our findings indicate that the proposed automated framework outperforms traditional data analysis methods in terms of accuracy, reduces the time and effort required for data analysis, and has better scalability for processing large datasets in real-time. Our results suggest that the proposed framework offers significant benefits for organizations seeking to improve their data analysis processes. However, we also note the importance of considering the costs and benefits of implementing the framework, as well as any ethical or legal implications. Further research is recommended to confirm the findings and to investigate the effectiveness of the proposed framework in different contexts and with different datasets.

ABSTRACT To our knowledge all the previous researches and studies for extracting the likely cause of emotion spikes was for comments and reviews with non-Arabic languages. Although, According to a study performed by Semiocast , Arabic was the fastest growing language on Twitter in 2011, and was the 6th most used language on Twitter in 2012. While a wide range of Arabic opinionated posts are broadcasted, research in the area of Arabic sentiment analysis remain sparse and show a very slow progress compared to that being carried out in other languages, mainly in English . For that, our work will be to identifying the likely causes of strong and sudden change of emotions within the temporal dimension of influential users’ emotion flow in Arabic Twitter we chose twitter because Twitter as a microblogging platform, receives over 500 million tweets worldwide every day as per 2016.These emotion spikes are the reaction of users toward certain events. Hence, our system will try to extracts keyphrases, which associated with each identified emotion spike, and passes them to an analyze step. Then the system will detect the named-entities and events or topics identification since the extracted keyphrases indicate a change on user’s emotions, and represent the causes of a particular emotion spike. 

Abstract: In this paper a new method for Full Reference Image Quality Assessment is presented. In current work the edge of the image is analyzed and the best scenario about the color is found. In first step the RGB, HSI and YCbCr color aretested. For each color the wavelet transform is applied and the edge of the images are extracted. With edge intensity specification the image quality assessment is tested. As result shown in this paper the PSNR, SROCC and Pearson is calculated. 

Information Communication Technologies (ICTs) provide an opportunity to meet the growing needs of rural areas. Many of the key features of ICT can be used to provide information and the requirements of people in rural areas. The digital divide considered is an important problem that countries face and it is much more complex than simply building out telecommunication networks and infrastructure. The divide is the result of a wide range of social factors, including but not limited to economy factors, education, literacy. Telecommunication infrastructure alone will not guarantee that users will be able to access and take advantage of services on the network. The paper begins with an introduction to the digital divide, and thus to highlight several successful initiatives provided by educational institutions and governmental organizations in Libya in the adoption of ICT. Finally, the paper provides some of the solutions proposed to reduce this divide.