ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

Absorption properties (Attenuation coefficient, the percentage of the reflection, and the percentage of absorption) in x-band have been investigated in this paper for novolac – alumina- graphite mixture. Using novolac as the host material, the samples are prepared with alumina concentrations (5%,10%,15%,20%) and graphite concentrations (5%,10%) with thickness equal to 2.2mm .Network analyzer produced by HP-8510 was used in this work to measure the attenuation coefficient. The samples (3, 5) have good attenuation of wave with bandwidth of frequencies. The maximum of attenuation is -25dB at frequency 10.28GHZ in sample (3) which has concentrations (80%novolac,10%alumina,and 5% graphite) and -24 dB at frequency 10.56GHZ in sample (5) whic

Management of Foreign Exchange Rate Exposure by Using Financial Hedging An Analytical Empirical Study The main purpose of this Research is to investigate the ability to reduce the  effect  of exchange rate fluctuation on firm value , by usage appropriate hedging strategies to provide the firms force to adopted with complex and highly uncertainty conditions , characteristic of the most of the financial markets  . The field of this study is the giant five Multinational on the world. Nokia, Toyota Motor, Intel , Coca Cola, Microsoft. practical analysis is provide the truth of all study's  hypothesis , and it is reach to many of conclusion, the most important of them is  Stem from unexpected fluctuation on nominal ex

An analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.

               Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95

The pumping station became widely used in many fields. Free surface vortices at intakes of pumps are not favorable. It may cause noise, excessive vibration, damage to the pumping structure, reduction in efficiency and flow for hydro-turbines, etc. One of the important problems encountered during the pump intake design is the depth of submergence and other design parameters to avoid strong free-surface vortices formation. This study aims to compute the critical submergence depth with some geometrical and hydraulic limitations by using Computational Fluid Dynamic (CFD) package. The mathematical model was validated with a laboratory model that had been conducted. The model of three intake pipes was investigated under five d

This study included the extraction properties of spatial and morphological basins studied using the Soil and Water Assessment Tool (SWAT) model linked to (GIS) to find the amount of sediment and rates of flow that flows into the Haditha reservoir . The aim of this study is determine the amount of sediment coming from the valleys and flowing into the Haditha Dam reservoir for 25 years ago for the period (1985-2010) and its impact on design lifetime of the Haditha Dam reservoir and to determine the best ways to reduce the sediment transport. The result indicated that total amount of sediment coming from all valleys about (2.56 * 10⁶ ton). The maximum annual total sediment load was about (488.22 * 10³ ton) in year 1988

We present a reliable algorithm for solving, homogeneous or inhomogeneous, nonlinear ordinary delay differential equations with initial conditions. The form of the solution is calculated as a series with easily computable components. Four examples are considered for the numerical illustrations of this method. The results reveal that the semi analytic iterative method (SAIM) is very effective, simple and very close to the exact solution demonstrate reliability and efficiency of this method for such problems.

Permeability is one of the essential petrophysical properties of rocks, reflecting the rock's ability to pass fluids. It is considered the basis for building any model to predict well deliverability. Yamama formation carbonate rocks are distinguished by sedimentary cycles that separate formation into reservoir units and insulating layers, a very complex porous system caused by secondary porosity due to substitute and dissolution processes. Those factors create permeability variables and vary significantly. Three ways used for permeability calculation, the firstly was the classical method, which only related the permeability to the porosity, resulting in a weak relationship. Secondly, the flow zone indicator (FZI) was divided reservoir into

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification