The main objective of this study is to measure the Impact of global financial crisis on some indicators of the Saudi Arabia's economy using the Mendel-Fleming model, the importance of the study applied by focusing on the theme of general equilibrium in the face of fluctuations in the global economy. Study used a descriptive approach and the methodology of econometrics to construct the model. Study used Eviews Program for data analysis. The Data was collected from the Saudi Arabian Monetary Agency, for the period (1997-2014).Stationery of the variables was checked by Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) unit roots tests. And also the co-integration

The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

The effects of three different additives formulations namely Lubrizol 21001, HiTEC 8722B and HiTEC 340 on the efficiency of VII namely OCP of three base lubricating oils namely 40 stock and 60 stock and 150 stock at four temperatures 40, 60, 80 and 100oC were investigated. The efficiency of OCP is decreased when blended with 4 and 8 wt% of Lubrizol 21001 for all the three base oil types. But it is increased when adding 4 wt% and 8 wt% of H-8722B in 40 stock. While for 60 stock and 150 stock the OCP efficiency decreased by adding 4 and 8 wt% of H-8722B. In the other hand, it is decreased with a high percentage by adding 4 and 8 wt% of H-340 for 60 stock and 150 stock and for 40 stock it is increased by adding 4 wt% of H-340 and decreased

Traction force and power requirement when performing primary tillage occupy the minds of almost farmers, this field research had aim to determine and calculate the pulling force of the most commonly used moldboard and chisel plows, the research conducted in silt clay loam for chisel and moldboard plows as the main factor, two depths of tillage 18 and 25 cm as a second factor and three speeds of tractor 2.55, 4.30 and 6.15 km.h-1 as a third factor. Moldboard plow recorded least traction force 7.550 kN, drawbar power 11.583 hp, power losses due to slippage 1.088 hp, power on the rear axle of the tractor 15.770 hp and brake horse power 17.495 hp. Chisel plow recorded best traction efficiency 76.217 % and total traction efficiency 68.659 %. Dep

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

لقد كان حرص المؤلف على إصدار هذا الكتاب نابعا ً من قناعة تامة بأن مجال التقويم والقياس بحاجة إلى كتاب علمي حديث يتناول عرض أدوات الاختبار والقياس والمتمثلة بالصدق والثبات ويتسم بالوضوح في التعبير عن المفاهيم والمصطلحات والأنواع لكل منها ليكون وسيلة مبسطة بأيدي الأساتذة والباحثين وطلبتي الدراسات العليا الماجستير والدكتوراه لإستخراج صدق وثبات الاختبارات والمقاييس بطرق إحصائية متقدمة من خلال إستخدام البرنا

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de