تشكل سوق الاوراق المالية ركناً اساسياً من اركان هيكل النظام التمويلي في النظم الاقتصادية المعاصرة، لما تقوم به هذه الاسواق من دور مهم في حشد المدخرات المحلية وتوجيهها في قنوات استثمارية تعمل على دعم الاقتصاد القومي وتزيد من معدلات الرفاهية الاقتصادية لافراده، فضلاً عن كونها مرأة للوضع الاقتصادي العام في البلاد.

ونتيجة للروابط القوية بين سوق الاوراق المالية والاقتصاد، عُدّ استقرار ونمو

Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he

The present study involves experimental analysis of the modified Closed Wet Cooling Tower (CWCT) based on first and second law of thermodynamics, to gain a deeper knowledge in this important field of engineering in Iraq. For this purpose, a prototype of CWCT optimized by added packing under a heat exchanger was designed, manufactured and tested for cooling capacity of 9 kW. Experiments are conducted to explore the effects of various operational and conformational parameters on the towers thermal performance. In the test section, spray water temperature and both dry bulb temperature and relative humidity of air measured at intermediate points of the heat exchanger and packing. Exergy of water and air were calculated by applying the exergy

Purpose: studying and analyzing the nature of uncertainty as part of strategy formulation, through analyzing the uncertainty faced by managers in the modern business environment characterized by high complexity and dynamism, though developing of an idea about the uncertainty cases and how enable the mind to understand these cases.

Methodology: It was the use of inductive and analytical approach, in order to study the accumulation of knowledge towards development areas that could contribute to strengthening the strategy formulation.

Findings: Mentoring the future will not make the success for business organization but thought business organization ability to developing share mental

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

In this paper, the Monte Carlo N-Particle extended  computer code (MCNP) were used to design a model of the European Sodium-cooled Fast Reactor. The multiplication factor, conversion factor, delayed neutrons fraction, doppler constant, control rod worth, sodium void worth, masses for major heavy nuclei, radial and axial power distribution at high burnup are studied. The results show that the reactor breeds fissile isotopes with a conversion ratio of 0.994 at fuel burnup 70 (GWd/T), and minor actinides are buildup inside the reactor core. The study aims to check the efficiency of the model on the calculation of the neutronic parameters of the core at high burnup.

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t

This study deals with the estimation of critical load of unidirectional polymer matrix composite plates by using experimental and finite element techniques at different fiber angles and fiber volume fraction of the composite plate.

            Buckling analysis illustrated that the critical load decreases in nonlinear relationship with the increase of the fiber angle and that it increases with the increase of the fiber volume fraction.

            The results show that the maximum value of the critical load is (629.54 N/m) at (q = 0°) and (V_f = 40 %) for the finite element method, while the minimum val