Advancements and challenges in Arabic sentiment analysis: A decade of methodologies, applications, and resource development.

The exponential growth of digital information, particularly user-generated content on social media and blogging platforms, has underscored the importance of sentiment analysis (SA). Arabic language sentiment analysis (ASA) involves identifying the orientation of ideas, feelings, emotions, and attitudes within Arabic text to determine whether they convey a positive, negative, or neutral sentiment. This paper presents a comprehensive review of the past decade, focusing on the utilization of SA in the Arabic language.

Experimental investigation of a dual mode antenna using characteristic mode analysis with enhanced directivity for GSM/5G applications.

In this article, a dual-mode, dual-polarized antenna designed using characteristic mode analysis (CMA) is described. An elliptical-shaped patch radiator is chosen with double slits on its minor axis. This design is based on mode separation from the circular patch into the elliptical patch.

Contribution to pulmonary diseases diagnostic from X-ray images using innovative deep learning models.

Pulmonary disease identification and characterization are among the most intriguing research topics of recent years since they require an accurate and prompt diagnosis. Although pulmonary radiography has helped in lung disease diagnosis, the interpretation of the radiographic image has always been a major concern for doctors and radiologists to reduce diagnosis errors. Due to their success in image classification and segmentation tasks, cutting-edge artificial intelligence techniques like machine learning (ML) and deep learning (DL) are widely encouraged to be applied in the field of diagnosing lung disorders and identifying them using medical images, particularly radiographic ones.

Empowering coffee farming using counterfactual recommendation based RNN driven IoT integrated soil quality command system.

Soil health is essential for whirling stale soil into rich coffee-growing land. By keeping healthy soil, coffee producers may improve plant growth, leaf health, buds, cherry and bean quality, and yield. Traditional soil monitoring is tedious, time-consuming, and error-prone.

Comparison activity of pure and chromium-doped nickel oxide nanoparticles for the selective removal of dyes from water.

The current study involves a synthesis of a composite of nickel oxide nanoparticles (NiONPs) with a chromium dopant to yield (Cr/NiONPs). Synthesis of nickel oxide was performed by the co-precipitation method. The synthesis of the composite was conducted by the impregnation method.