يسعى هذا البحث الى تقديم اطار عملي ونظري حول موضوع "تأثير الاقتصاد المنزلي في تعزيز الاداء العالي" وتم اختبار مخطط الدراسة الفرضي في القطاع التعليمي الحكومي في محافظة البصرة ,ويتضمن عدد من تشكيلات الجامعة التقنية الجنوبية. واستخدمت الاستبانة والمقابلة الشخصية كأسلوب لجمع البيانات للدراسة وكان حجم العينة114 موظف. وقد استخدمت عدد من الاساليب الاحصائية لاختبار فرضيات الدراسة. واظهرت النتائج بأن هناك تأثير ايج

An experimental work has been conducted on wall attachment fluidics amplifiers, one of them to study the effect of output pressure or load on the amplifier performance. The output load has been simulated as a piston connected to the device output and the piston can be loaded accordingly. The results shows that the output volume flow rate increases as the supply pressure increases under different load and the output pressure remains constant as the supply pressure increases under constant load.

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

Polarization is an important property of light, which refers to the direction of electric field oscillations. Polarization modulation plays an essential role for polarization encoding quantum key distribution (QKD). Polarization is used to encode photons in the QKD systems. In this work, visible-range polarizers with optimal dimensions based on resonance grating waveguides have been numerically designed and investigated using the COMSOL Multiphysics Software. Two structures have been designed, namely a singlelayer metasurface grating (SLMG) polarizer and an interlayer metasurface grating (ILMG) polarizer. Both structures have demonstrated high extinction ratios, ~1.8·103 and 8.68·104 , and the bandwidths equal to 45 and 55 nm for th

In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste

The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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