The aim of this paper is to design feed forward neural network to determine the effects of
cold pills and cascades from simulation the problem to system of first order initial value
problem. This problem is typical of the many models of the passage of medication throughout
the body. Designer model is an important part of the process by which dosage levels are set.
A critical factor is the need to keep the levels of medication high enough to be effective, but
not so high that they are dangerous.

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

Some researchers are interested in using the flexible and applicable properties of quadratic functions as activation functions for FNNs. We study the essential approximation rate of any Lebesgue-integrable monotone function by a neural network of quadratic activation functions. The simultaneous degree of essential approximation is also studied. Both estimates are proved to be within the second order of modulus of smoothness.

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

The aim of this study was to measure the effectiveness of a proposed program to develop the creative abilities of the students of Tabuk University and its impact on the creative output of the NEOM project. The sample of the study consisted of (50) university students divided into two groups: an experimental group of 25 students who receive the proposed training program, and control group of (25) students.

 To achieve these objectives, the researcher designed and developed tools to collect the required data, which were verified their validity and reliability.

The descriptive statistics of mean, standard deviations, correlation coefficient, T test for the associated sample were used in the analysis of the results of th

The purpose of this research is to identify the youth issues in Talk Shows in the Iraqi satellite channels via monitoring a sample of episodes of the Talk Shows  episodes which are concerned and analyzed the youth issues in the Iraqi satellite channels, namely, «Hala Shabab Program» at Al-Iraqia satellite Channel and «Shabab wa Banat Program» at Al-Sumaria satellite Channel by recording and re-watching them again. This research is classified as one of descriptive researches. The survey method was adopted in this study.

For this purpose, the researcher prepared an analysis form. The researcher de

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb of 4-(4-Nitrobenzeneazo) 3-Aminobenzoic Acid from aqueous solutions has been investigated through columnar method. The azo dye adsorption found to be dependent on adsorbent dosage, initial concentration and contact time. All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.), at room temperature (25±2) °C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monolayer adsorption capacity is 6.4066 mg Azo ligand per 1g calcined Montmorillonite. The experiments showed that highest removal rate 90.5 % for azo dye at pH 5.5.The

ABSTRACT : A new ligand [ 2- (3-acetylthioureido)-3-phenylpropanoic acid (APA) is synthesized by reaction of acetyl isothiocyanate with phenylalanine (1:1). It is characterized by micro elemental analysis (C.H.N.S.), FT-IR, (UV-Vis) and 1H and 13CNMR spectra. Some metals ions complexes of this ligand were prepared and characterized by FT-IR, UV-Visible spectra, conductivity measurements, magnetic susceptibility and atomic absorption. From results obtained, the following formula [M(APA)2] where M2+ = Mn, Co, Ni, Cu, Zn, Cd and Hg, the proposed molecular structure for these complexes as tetrahedral geometry, except copper complex is has square planer geometry.