Mefenamic acid belongs to non-steroidal anti-inflammatory drugs that are used widely for the treatment of analgesia. Our aim from this study is to establish a new assay for the quantitative determination of mefenamic acid (MFA) in the pharmaceutical sample by two sensitive and rapid flow injection-fluorometric methods. A homemade fluorometer was used in fluorescence measurements, which using solid-state laser diode 405 and 532 nm as a source, combined with a continuous flow injection technique. The first method depends on the effect of MFA on calcein blue (CLB) fluorescence at 405 nm. Another method is a study of rhodamine-6G (Rh-6G) fluorescence after adding MFA, and recording at 532 nm. Optimum parameters as fluorescent dye concen

Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the pipelines either during operation of the vacuum unit or when the tower out of operation.  Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O₂ from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves re

Water injection equipments such as pipelines, which are used in the second recovery of oil in the Al-Ahdeb wells, suffer from the corrosion in water during maintaining vacuum deoxygenated tower that used to decrease concentration of the dissolved oxygen gas in the water from 6.2-9.1 ppm to o.5 ppm. This study involved calculation the corrosion rates of the internal surfaces of the
pipelines either during operation of the vacuum unit or when the tower out of operation. Finally, find the solution by one of the following suggestions. In the first suggestion removal of the dissolved O2 from water is achieved by increasing the dosage of the oxygen scavenger (sodium sulphite). The second suggestion involves removing the dissolved O2 from w

The aim of this work is to study the influence of the type of fiber glass –mat on fatigue behavior of composite material which is manufactured from polyester and E-glass (woven roving, chopped strand mat (CSM)) as a laminate with a constant fiber volume fraction (VF) of 33%. The results showed that the laminates reinforced with E-glass (woven roving) [0/90, ±45.0/90] and [0/90, CSM, 0/90] have lower fatigue strength than the laminates reinforced with E-glass [0/90]₃,[CSM]₃ and [CSM, 0/90, CSM]  although they had different tensile strength; the best laminate was [0/90]₃ .

In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a