The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This study was for searching for Cholera Bacteria serotype which causes epidemiology Cholera in the 2007 in a fast method which contains (Rapid Visual Test) (Crystal V.C.) which was used for the first time in Iraq to diagnosis of Cholera Bacteria & compared with the traditional bacteriology method. The Cholera disease is one of the most dangerous epidemiological diseases which lead to death with a percentage of (50 – 70) % in the severe cases for untreated patients . For this purpose, 100 samples of stool from the patients from a (13) hospitals in Baghdad Governorate in the period from August to the end of December. The Cholera was diagnosis in two methods, 1st method was the fast method using the nitrocellulose which is coated with anti-

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

It is a well-known fact that publishing companies spend much money, time and energy in designing their book covers to attract potential customers. As the first thing people do when they buy or intend to buy a book is looking at its front cover. However, if there is a need to know more about the book, people usually look at the information on its back cover. This paper attempts to explore the persuasive function of blurbs beyond the constraints of the academic domain and consequently their connection with advertising discourse in two main sections: The first presents the concept of blurb and its structure while the second defines persuasion and shows the most prominent strategiesused in blurbs. Finally, this paper gives the conclusion tha

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used