Polyaniline organic Semiconductor polymer was prepared by oxidation polymerization by adding hydrochloric acid concentration of 0.1M and potassium per sulfate concentration of 0.2M to 0.1M of aniline at room temperature, the polymer was deposited at glass substrate, the structural and optical properties were studies through UV-VIS, IR, XRD measurements, films have been operated as a sensor of vapor  H₂SO₄ and HCl  acids.

Pulsatile drug delivery systems are time-controlled dosage forms which are designed to release the active pharmaceutical ingredient after a predetermined lag time to synchronize the disease circadian rhythm. A migraine shows circadian rhythm with a marked increase in attacks between 6 a.m. and 8 a.m.

Sumatriptan is a selective agonist at serotonin (5-Hydroxy tryptamine1  (5-HT1))receptors, is an effective treatment for acute migraine attacks.

The aim of this work is to prepare time-controlled press-coated tablet with a lag time of 5.45 hrs.

Six formulas of fast dissolving core tablets and three formulas of press-coated tablets were prepared by using direct compression method using different variables to prepa

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Analysis of Covariance consider to be quite important procedure to reduce the effect of some independents factors before going through the experiment.

By this procedure we can compare variances causes from the difference between treatments and error term variance of they are equals or less than consider to be not significant, otherwise if is significant.

We carry on with this comparison until we find the greatest covser for the significant variance flam the treatments.

There are methods can be used like least significant difference method, Duncan method and Turkeys' w-procedure and Student Newman.

Key Word: Analysis of variatio