This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

The effective surface area of drug particle is increased by a reduction in the particle size. Since dissolution takes place at the surface of the solute, the larger the surface area, the further rapid is the rate of drug dissolution. Ketoprofen     is class II type drug according to (Biopharmaceutics Classification System BCS) with low solubility and high permeability. The aim of this investigation was to increase the solubility and hence the dissolution rate by the preparation of ketoprofen     nanosuspension using solvent evaporation method. Materials like PVP K30, poloxamer 188, HPMC E5, HPMC E15, HPMC E50, Tween 80 were used as stabilizers in perpetration of differ

In this paper to isolate and study the properties of the cyclooxygenase-2 (EC: 1.14.99.1) enzyme in the blood of a patient suffering from rheumatoid arthritis and study the effect of natural products of the Soapwort on the activity of purified enzyme. The study involves taking 30 ml of blood from an adult woman 40 years old, who suffers from rheumatoid arthritis disease for 13 years. Serum is separated and subjected to a series of purification processes including: precipitation by ammonium sulfate, filtration by centrifugation radiator, dialysis in presence of ammonium bicarbonate, separation using the technology of ion exchange, lipholization and then estimating approximate molecular weight of the enzyme using gel filtration techni

This study was conducted to prepare protein concentrates from AL-Zahdidate’s pits by using alkaline methods where the chemical composition of the pits were (7.30, 1.04, 5.80, 8.68 and 77.19) % for each of the moisture, ash, protein, fat and carbohydrates respectively and the chemical composition of the concentrate protein was (6.62, 4.10, 26.70, 0.93, and 58.65) % respectively. The content of protein concentrate from the metallic elements (144.07, 25.11, 15.02, 0.49, 0.59, 0.27, 0.22 and 234.6) mg/ 100 g each of potassium, magnesium, calcium, iron, manganese, copper, zinc and phosphorus respectively. The results of SDS-PAGE showed five bands with weights molecular ranged between 11000-70000 Dalton. Give the biscuit which contain protei

     One hundred samples of root canal bacteria were isolated  from patients teeth with primary and secondary infected root canal from all the ages . Biochemical and microscopial tests were done for identification of these isolates. Twenty four isolates were confirmed as       E. faecalis species by using these tests. Genetic diagnosis for the all isolates was also done by using polymerase chain reaction ( PCR ). Thirty two isolates were confirmed to  belong to E. faecalis species by using this test.

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

The -mixing of  - transition in Er 168 populated in Er)n,n(Er 168168  reaction is calculated in the present work by using a2- ratio method. This method has used in previou studies [4, 5, 6, 7] in case that the second transition is pure or for that transition which can be considered as pure only, but in one work we applied this method for two cases, in the first one for pure transition and in the 2nd one for non pure transitions. We take into accunt the experimental a2- coefficient for p revious works and -values for one transition only [1]. The results obtained are, in general, in agood agreement within associated errors, with those reported previously [1], the discrepancies that occur are due to inaccuracies existing

The - M ultiple mixing ratios of -transitions from levels of 56Fe populated in 56 56 Fe n n Fe ( , )  reactions are calculated by using const. S.T.M. This method has been used in other works [3,7] but with pure transition or with transitions that can be considered as pure transitions، in our work we used This method for mixed  - transitions in addition to pure  - transitions. The experimental angular distribution coefficients a2 was used from previous works [1] in order to calculet - values. It is clear from the results that the - values are in good agreement or consistent, within associated errors, with those reported previously [1]. The discrepancies that occur are due to inaccuracies existing in the expe

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de