Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

The present work aimed to study the efficiency of nanofiltration (NF) and reverseosmosis (RO) process for water recovery from electroplating wastewater and study the factors affecting the performance of two membrane processes. Nanofiltration and reverse osmosismembranes are made from polyamide as spiral wound module. The inorganic materials ZnCl 2 CuCl2 .2H2O, NiCl.2.6H2O and CrCl3.6H2O were used as feed solutions. The operating parametersstudied were: operating time, feed concentrations for heavy metal ions, operating pressure, feed flow rate, feed temperature and feed pH. The experimental results showed, the permeateconcentration increased and water flux decreased with increase in time from 0 to 70 min. Thepermeate concentrations incre

Abstract

Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthio- benzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L^/)as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar const

Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.

Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.