Arabic language processing with artificial intelligence has evolved significantly in the past decades, from traditional rule- and dictionary-based techniques, through statistical models to modern deep and transformer models. This review intends to present an overview of the most well-known Arabic models as well as datasets used for its training, and the main practical applications such as sentiment analysis, machine translation, speech recognition, and smart assistant. AI-based Arabic NLP has had good progress in the previous decades, from rule and dictionary-based approaches to statistical methods and deep transformative learning models nowadays. In addition to it, the most popular state-of-the-art models that are fine-tuned for the Arabi

The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive ex

Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope

The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien

Copper (I) complex containing folic acid ligand was prepared and characterized on the basis of metal analyses, UV-VIS, FTIR spectroscopies and magnetic susceptibility. The density functional theory (DFT) as molecular modeling calculations was used to determine the donor atoms of folic acid ligand which appear clearly at oxygen atoms binding to hydrogen. Detection of donation sights is supported by theoretical parameters such as geometry, mulliken population, mulliken charge and HOMO-LUMO gap obtained by DFT calculations.

    Taurodontism is a rare developmental dental anomaly marked by apical displacement of the pulpal floor, enlarged pulp chambers, and root bifurcation or trifurcation near the apex. Its etiology involves genetic mutations, syndromic associations, or developmental disturbances of Hertwig’s epithelial root sheath. Diagnosis relies mainly on radiographic assessment, with CBCT offering superior accuracy, and indices such as Shaw’s and Shifman’s aiding classification. Clinically, taurodontism complicates endodontic, surgical, orthodontic, and restorative procedures and may indicate underlying systemic disorders. Early recognition and interdisciplinary planning are crucial to optimizing patient outcomes. DOI: ht

Optimization of well placement plays a considerable role in the production and maximizing the net present value of the investment of oil field developments. However, the application of the optimization techniques in well placement developments is so complicated because many decision variables, objective functions, and constraints are involved in the well placement optimization case. Furthermore, many computational techniques; conventional and non-conventional, have been utilized to optimize well placement operations. This study displays the advancement of the optimization methods applied in the well placement. Subsequently, the study assorted the applied optimization methods, and it demonstrates the restriction and the range of implementati

The demand for electronic -passport photo ( frontal facial) images has grown rapidly. It now extends to Electronic Government (E-Gov) applications such as social benefits driver's license, e-passport, and e-visa . With the COVID 19 (coronavirus disease ), facial (formal) images are becoming more widely used and spreading quickly, and are being used to verify an individual's identity, but unfortunately that comes with insignificant details of constant background which leads to huge byte consumption that affects storage space and transmission, where the optimal solution that aims to curtail data size using compression techniques that based on exploiting image redundancy(s) efficiently.