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 Arabic language and their corpora of training data will be considered as well as major applications such as Sentiment Analysis, Machine Translation, Speech Recognition, and Virtual Assistant. This article review outlines the necessity for investment in language resources and advanced models to improve AI systems’ ability to accurately understand Arabic natural language, a contribution that will support real-life applications and smart services associated with its present formalized variant of AI model capabilities.
In 1939, the Japanese scientist Michio Takaoka first mentioned resveratrol from Veratrum grandiflorum O. Loes. Majority of plants, such as grapes, berries, and peanuts, are significant sources of resveratrol, a well-known polyphenolic. resveratrol (RV) is noted for its links to several health care benefits, including glucose metabolism, anti-aging, cardioprotective, neuroprotective, antitumor, antidiabetic, and antioxidant effects. Importantly, there have been reports of promising therapeutic qualities in atherosclerosis, dementia, and various malignancies. These properties are controlled through a number of cooperative techniques, which control inflammation besides the effects of oxidative stress and cell death. However, circulating resver
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Abstract
This research aims to study and improve the passivating specifications of rubber resistant to vibration. In this paper, seven different rubber recipes were prepared based on mixtures of natural rubber(NR) as an essential part in addition to the synthetic rubber (IIR, BRcis, SBR, CR)with different rates. Mechanical tests such as tensile strength, hardness, friction, resistance to compression, fatigue and creep testing in addition to the rheological test were performed. Furthermore, scanning electron microscopy (SEM)test was used to examine the structure morphology of rubber. After studying and analyzing the results, we found that, recipe containing (BRcis) of 40% from th
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Over the past ten years, tumor markers have played an increasingly important role in clinicaloncology. This trend is expected to continue as technology advances and our knowledge of thehuman body and disease processes grows. In the treatment of cancer, tumor markers are widelyused for a variety of purposes, including screening, selecting a management strategy,determining the prognosis, and post-therapy follow-up. A comprehensive of the fundamentalsof pathophysiology and identification strategies for each specific malignancy is necessary fortheir prudent application in clinical practice. Oncology's use of cancer biomarkers hastransformed the way that cancer is treated, and led to notable improvements in patient outcomesand cancer tre
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The rapid sprawl in urban areas caused by excessive production and consumption of goods (as driven by local poor social choices) has inevitably resulted in a major burden due to environmental degradation worldwide. Unfortunately, these traditional models of urban planning fail to properly account for the intricacies that permeate a modern city and are deficient in terms of their approach as they shape themselves within an environment largely divorced from natural systems, resulting in vast mismanagement of resources, guiding cities down trajectories where growth destroys both physical and cultural landscapes. As cities suffer from increasing scarcity, we advocate for regeneration and resilience to be embedded in advanced urban design approa
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Mixing this strategy with a qualitative research design and an idea known as AI-supported journalism, the paper is going to approach the requirements of how AI technologies may transform journalism content and culture in a way beyond what one anticipates; therefore, enabling more of it to reach an audience. The current research used descriptive research design to investigate the potential applications of the AI tools that mediate civilizational conversation and a structured questionnaire to media professionals. AI-driven journalism can promote peaceful cohabitation and mutual respect and thus act as a bridge between cultures, the research said. The piece even goes on to mention the need for media establishments and civil soc
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In recent years, literary studies have witnessed a remarkable shift towards employing digital technologies, particularly artificial intelligence tools, in analyzing literary texts and exploring their linguistic and semantic structures. This trend has provided researchers with new possibilities for understanding texts in quantitative and qualitative ways that transcend traditional methods based solely on critical reading. The current research aims to introduce professors and students of Arabic to artificial intelligence tools that contribute to the analysis of literary texts, focusing on exploring their mechanisms for studying style, meaning, structure, and emotion. It also seeks to highlight the most prominent challenges facing researchers
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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