A simple all optical fiber sensor based on multimode interference (MMI) for chemical liquids sensing was designed and fabricated. A segment of coreless fiber (CF) was spliced between two single mode fibers to buildup single mode-coreless-single mode (SCS) structure. Broadband source and optical signal analyzer were connected to the ends of SCS structure. De-ionized water, acetone, and n-hexane were used to test the performance of the sensor. Two influence factors on the sensitivity namely the length and the diameter of the CF were investigated. The obtained maximum sensitivity was at n-hexane at 340.89 nm/RIU (at a wavelength resolution of the optical spectrum analyzer of 0.02 nm) when the diameter of the CF reduced from 125 μm to 60 μ

Oil flow lines are used to transport oil and its derivatives from a well over long distances, and because oil wells produce other potentially corrosive products, such as carbon dioxide and Hydrogen sulfide, it is necessary to take methods to protect the pipeline from corrosion. One of these methods is the use of corrosion inhibitors in this study. Prepare 5-acetyl-2-anilino-4-dimethylaminothiazole and test it as a corrosion inhibitor on a sample of the Rumaila flow line at a constant temperature 25°C in (3.5%) NaCl and (3.5%) KCl solution in the absence and presence of different concentrations of inhibitor (0 mM, 0.01 mM, 0.03 M, 0.05 mM). by using liner polarization (Tafel slope). The inhibiter exhibited the best performance at hi

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

يعد كتاب(الفهرست) لإبن النديم أول كتاب جامع في القرن الرابع الهجري ،حصر الكتب و المؤلفات العربية و رصدها في مجالات العلم و المعرفة و الثقافة و الفن ،و اللغة والأدب و الشعر بما يكشف عن النشاط الفكري ، و الحياة العقلية و العلمية للعصر .

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

This work deals with the production of light fuel cuts of (gasoline, kerosene and gas oil) by catalytic cracking treatment of secondary product mater (heavy vacuum gas oil) which was produced from the vacuum distillation unit in any petroleum refinery. The objective of this research was to study the effect of the catalyst -to- oil ratio parameter on catalytic cracking process of heavy vacuum gas oil feed at constant temperature (450 °C). The first step of this treatment was, catalytic cracking of this material by constructed batch reactor occupied with auxiliary control devices, at selective range of the catalyst –to- oil ratio parameter (  2, 2.5, 3 and 3.5) respectively.  The conversion of heavy vacuum gas