The water injection of the most important technologies to increase oil production from petroleum reservoirs. In this research, we developed a model for oil tank using the software RUBIS for reservoir simulation. This model was used to make comparison in the production of oil and the reservoir pressure for two case studies where the water was not injected in the first case study but adding new vertical wells while, later, it was injected in the second case study. It represents the results of this work that if the water is not injected, the reservoir model that has been upgraded can produce only 2.9% of the original oil in the tank. This case study also represents a drop in reservoir pressure, which was not enough to support oil production

Ondansetron hydrochloride (ONH) is a very bitter, potent antiemetic drug used for the treatment and/or prophylaxis of chemotherapy or radiotherapy or postoperative induced emesis. The objective of this study is to formulate and evaluate of taste masked fast dissolving tablet (FDTs) of ONH to increase patient compliance.

 ONH taste masked granules were prepared by solid dispersion technique using Eudragit E100 polymer as an inert carrier. Solvent evaporation and fusion melting methods were used for such preparation.

Completely taste masking with zero release of drug in phosphate buffer pH 6.8was obtained from granules prepared by solvent evaporation method using drug: polymer ratio of 1:2, from which four formulas pas

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

In unpredicted industrial environment, being able to adapt quickly and effectively to the changing is key in gaining a competitive advantage in the global market. Agile manufacturing evolves new ways of running factories to react quickly and effectively to changing markets, driven by customized requirement. Agility in manufacturing can be successfully achieved via integration of information system, people, technologies, and business processes. This article presents the conceptual model of agility in three dimensions named: driving factor, enabling technologies and evaluation of agility in manufacturing system. The conceptual model was developed based on a review of the literature. Then, the paper demonstrates the agility

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa

The present research deals with the spatial variance analysis in Jwartadistrict and conducting a comparison on the spatial and seasonal changes of the vegetation cover between (2007-2013) in order to deduce the relationship between the vegetation density and the areas which are exposed to the risk of water erosion by using Plant Variation Index  NDVI) C (coefficient and by using Satellite images of Landsat satellite which are taken in 2/7/2007 and Satellite images of Landsat satellite taken in 11/1/ 2013, the programs of remote sensitivity and the Geographic Information Systems.

    The study reveals that there is a variance in the density of vegetation cover of the area under study betwee 2007 and 2013. Howev

This research was aimed to study the efficiency of microfiltration membranes for the treatment of oily wastewater and the factors affecting the performance of the microfiltration membranes experimental work were includes operating the microfiltration process using polypropylene membrane (1 micron) and ceramic membrane (0.5 micron) constructed as candle; two methods of operation were examined: dead end and cross flow. The oil emulsion was prepared using two types of oils: vegetable oil and motor oil (classic oil 20W-50). The operating parameters studied are: feed oil concentration 50 – 800 mg/l, feed flow rate 10 – 40 l/h, and temperature 30 – 50 oC, for dead end and cross flow microfiltration.
It was found that water flux decrea