Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

miRNAs regulate protein abundance and control diverse aspects of cellular processes and biological functions in metabolic diseases, such as obesity and diabetes. Lethal-7(Let-7) miRNAs specifically target genes associated with diabetes and have a role in the regulation of peripheral glucose metabolism. The present study aimed to describe the gene expressions of the let-7a gene with the development of diabetes in Iraq and the difference in the expression of this gene in patients with diabetes and healthy individuals. The association between age and gender with the development of diabetes was studied in this study and the results were compared with those of healthy individuals in the group of control. Based on the obtained results, there was

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

The study found a number of results. The most prominent were the low married during the years of the study in 1997-2012. The study also showed the level of administrative units that the percentage of widows and single rise in urban and rural decline. This is due to the different nature of urban and rural society of the behavior and social habits and traditions.As the proportion of divorced and unmarried are decreased in urban and increase proportion in the countryside, and this is due to the influence of the rural population in the urban centers. As well as the study showed that there was a significant effect of the economic and social factors and other factors on marital status on its parts in the study area.

Huge number of medical images are generated and needs for more storage capacity and bandwidth for transferring over the networks. Hybrid DWT-DCT compression algorithm is applied to compress the medical images by exploiting the features of both techniques. Discrete Wavelet Transform (DWT) coding is applied to image YCbCr color model which decompose image bands into four subbands (LL, HL, LH and HH). The LL subband is transformed into low and high frequency components using Discrete Cosine Transform (DCT) to be quantize by scalar quantization that was applied on all image bands, the quantization parameters where reduced by half for the luminance band while it is the same for the chrominance bands to preserve the image quality, the zig