Ultimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0

A new method based on the Touchard polynomials (TPs) was presented for the numerical solution of the linear Fredholm integro-differential equation (FIDE) of the first order and second kind with condition. The derivative and integration of the (TPs) were simply obtained. The convergence analysis of the presented method was given and the applicability was proved by some numerical examples. The results obtained in this method are compared with other known results.

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

Orthophoto provides a significant alternative capability for the presentation of architectural or archaeological applications. Although orthophoto production from airphotography of high or lower altitudes is considered to be typical, the close range applications for the large-scale survey of statue or art masterpiece or any kind of monuments still contain a lot of interesting issues to be investigated.

In this paper a test was carried out for the production of large scale orthophoto of highly curved surface, using a statue constructed of some kind of stones. In this test we use stereo photographs to produce the orthophoto in stead of single photo and DTM, by applying the DLT mathematical relationship as base formula in differenti

Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve