Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content

The wake potential and wake phenomena for swift proton in an amorphous carbon target were studied by utilising various dielectric function formalisms, including the Drude dielectric function, the Drude–Lorentz dielectric function and quantum dielectric function. The Drude model results exhibited a damped oscillatory behaviour in the longitudinal direction behind the projectile; the pattern of these oscillations decreases exponentially in the transverse direction. In addition, the wake potential extends slightly ahead of the projectile which also depends on the proton coordinate and velocity. The effect of electron binding on the wake potential, characterised by the ratio to 0.1, has been studied alongside the Drude–Lorentz dielectric

The High Modulus Asphalt Concrete Mixture (HMACM) or (EME) (Enrobes a Module Eleve) developed in France, since, 1980 by Laboratories Central des Ponts et Chaussees (LCPC). Due to the increasing in traffic intensity and axle loading this type of mixing were suitable for pavement subjected to heavy duty. Experiments showed that EME mixtures have an excellent moisture damage resistance permanent deformation, fatigue cracking and reducing costs of maintenance and a significant reduction in thickness of pavement. Because of the high stiffness of EME mixes, the stresses transformed to the bottom laid layer by repeated traffic wheel loads were reduced effectively. This study intend to focus the light into the possibility of producing asphalt mixtu

This study aimed to improve the microencapsulation technique using a type coating the encapsulation Layer by Layer, which provide the best protection for life Lactobacillus casei in the extrusion method and use the microencapsulation of materials of the protein concentrated by protein 80% and the coating with alginate and chitosan have the results showed the variation in the difference of the binding process encapsulation yield among the types of coating through. by studying of these the effect o stability of the bio probiotic free cell and the three types coated towards three different concentrations from bile salts 0, 0.3, 0.5 and 0.7% when the periods of time different of zero and two and three hours at incubation the recorded

The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Research Summary


The research revolves around the collection of pending hadiths on Abdullah bin Amr bin Al-Aas, may God be pleased with them, and it is required in these hadiths that they be among those in which there is no room for diligence, such as telling about unseen matters, signs of the Hour, or a statement of virtue and reward for obedience, or punishment for disobedience.

The research consists of an introduction, two topics, and a conclusion of the first topic in the translation of Abdullah bin Amr bin Al-Aas, and the second topic, the pending hadiths of Abdullah bin Amr bin Al-Aas, may God be pleased with them, in which there is no room for diligence in collecting and studying

At the end of this rese