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.

The ground state proton momentum distributions (PMD) and elastic charge form
factors for some odd 1f  2p shell nuclei, such as , , 59 63Co Cu and Cu 65 have been
studied using the Coherent Density Fluctuation Model and formulated by means of
the fluctuation function (weight function) ( ) .
2
f x The fluctuation function has been
connected to the charge density distribution of the nuclei and determined from the
theory and experiment result. The feature of the long-tail behavior at high
momentum region of the PMD has been calculated by both the theoretical and
experimental fluctuation functions. It is found that the inclusion of the quadrupole
form factors ( ) 2 F q C in all nuclei under study, which are de

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

Periodontitis is a multifactorial chronic inflammatory disease that affects tooth-supporting soft/hard tissues of the dentition. The dental plaque biofilm is considered as a primary etiological factor in susceptible patients; however, other factors contribute to progression, such as diabetes and smoking. Current management utilizes mechanical biofilm removal as the gold standard of treatment. Antibacterial agents might be indicated in certain conditions as an adjunct to this mechanical approach. However, in view of the growing concern about bacterial resistance, alternative approaches have been investigated. Currently, a range of antimicrobial agents and protocols have been used in clinical management, but these remain largely non-v

The tested isolate of Rhizobium leguminosarum bv. viciae was isolated from root nodules of vicia faba plant from Baghdad ,the isolated bacteria was examined for bioemulsifier production when growing in mineral salt medium that containing 1% sunflower oil as sole carbon source . Rhizobium isolate was able to produce bioemulsifier with initial emulsification index E24% was 38%. Many of physical and nutritional cultural conditions for optimum emulsifier production was examined including : pH , temperature ,incubation period ,carbon and nitrogen source. The maximum bioemulsifier production form Rhizobium isolate was 64.5% when bacteria growing in mineral salt medium with pH 9 ,incubated at temperature 30 ºC , incubation period was 10 days ,

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

This research deals with the study of top soil electrical conductive regions located within Baghdad City. The research included measuring the dissolved soil material extraction Electrical Conductivity (EC) with an aqueous solution for the top (0-30 cm) soil layer of the study area. As the electrical conductivity values increase by increasing the amount of dissolved salts in principle, we can consider that the aim of this research is to predict the amount and distribution of (soil contamination with salts) which is represented by the (Salt Index), this factor calculated for each soil representative sample taken from the region with a depth of (30 cm). Laboratory (EC) test values measured by the use of solutions (EC) digital meter for the ex

A total of 47 samples were collected from different clinical specimens (urine, wounds, burns, sputum, blood, stools) during the period from November 2013 to
January 2014, only 18 isolates (38.29%) were identified as Klebsiella pneumoniae ,11isolates (23.4%) as E. coli , 9 isolates (19.1%) as S. aureus, 3isolates (6.3%) as Psedomonase spp., 2 isolates (4.2 %) as K. terrigena and 4 isolates (8.5%) as K. oxytoca. The results were shown the elevation of K. pneumoniae percentage among the bacterial isolates depending on cultural, microscopically, biochemically characteristics and confirmed by using the API 20E and VITEK 2 system . Also K. pneumoniae isolates were more frequently in sputum samples then burns, stools , urine, wounds ,and blo

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul