The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

The issue of nuclear proliferation is one of the most vital issues as it reflects a form of dealing in the field of international relations. Therefore, the Middle East region has taken great interest in reducing the levels of nuclear armament and acquiring nuclear power within the strategic framework of the international and regional powers. The establishment of a nuclear-weapon-free zone in the Middle East region is currently one of the most important international and regional arrangements for controlling the levels of nuclear proliferation and attempting to build a state of stability and balance. In the Middle East and the world. The importance of the research comes from the fact that it deals with an important and vital issue

Many of accurate inertial guided missilc systems need to use more complex mathematical calculations and require a high speed processing to ensure the real-time opreation. This will give rise to the need of developing an effcint

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

We study the physics of flow due to the interaction between a viscous dipole and boundaries that permit slip. This includes partial and free slip, and interactions near corners. The problem is investigated by using a two relaxation time lattice Boltzmann equation with moment-based boundary conditions. Navier-slip conditions, which involve gradients of the velocity, are formulated and applied locally. The implementation of free-slip conditions with the moment-based approach is discussed. Collision angles of 0°, 30°, and 45° are investigated. Stable simulations are shown for Reynolds numbers between 625 and 10 000 and various slip lengths. Vorticity generation on the wall is shown to be affected by slip length, angle of incidence,

The study was conducted at the fields of the Department of Horticulture and Landscape Gardening, College of Agriculture, University of Baghdad " Abu Ghraib" during the growing seasons 2013-2014 to Evaluate the Vegetative growth , yield traits and genetic parameter of some tomato mutants. Results showed significantly increased of plant height in M6-2 mutant 245cm in Comparison with M6- 3 130 cm . M6-4 mutant significantly increasing of floral clusters 13 . Mutant M6-3 showed significantly increasing the average of, fruit weight 125.9g and plant yield 7.17 kg.plant-1 as comparison with M6-2 which showed decreasing of average of fruit weight and plant yield 79.40g and 4.38 kg.plant-1 respectively. Also results showed the highest Genetic variat

Twelve species from Brassicaceae family were studied using two different molecular techniques: RAPD and ISSR; both of these techniques were used to detect some molecular markers associated with the genotype identification. RAPD results, from using five random primers, revealed 241 amplified fragments, 62 of them were polymorphic (26%).

    ISSR results showed that out of seven primers, three (ISSR3, UBC807, UBC811) could not amplify the genomic DNA; other primers revealed 183 amplified fragments, 36 of them were polymorphic (20%). The similarity evidence and dendrogram for the genetic distances of the incorporation between the two techniques showed that the highest similarity was 0.897 between the va