Abstract

               The research aimed to prepare an audit program focusing on the activities of municipal institutions related to the environmental dimension as one of the dimensions of sustainable development, and applying the program for the purpose of preparing an oversight report related to assessing the impact of the activities of municipal institutions on the environmental reality as the main channel through which municipal institutions contribute to achieving the part related to it. Among the requirements of sustainable development, the proposed program was prepared and applied to the institutions affiliated to the Directorate of Mu

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30^o, 45^o and 60^o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho

In accounting studies, more than one method is used to measure income and balance sheets elements. One of these methods is called the fair value, which use to determine the assets and liabilities ad it includes the benefits or self-satisfaction ability. This paper aims to focus on the importance of fair value as a basis of accounting measurement and its effects to achieve the relevant characteristics by using the equation is used by (Kythreotis) in his research, And Also , Editing this equation depending on the financial data and information of Iraqi Banks as a case.

Osteoporosis is a prevalent systemic metabolic disorder characterized by a reduction in bone mass and bone density, damage in microstructure of bone tissue, and raised bone fragility causing of fracture susceptibility. This study included 189 Iraqi adults aged 45–75 years, evaluating serum levels TGF-β3 and WNT5A across three groups: healthy individuals (n = 31) as control, those with primary osteoporosis/osteopenia (n = 61), and with comorbidity-related osteoporosis (linked to β-thalassemia, parathyroid disorders or diabetes; n = 97). Among those, β-thalassemia-associated osteoporosis patients showed the most distinct decrease in bone mineral density (0.57 ± 0.078 g/cm², p < 0.0001) along with marked increases in WNT5A (0.89 ± 0.68

The paper aims at initiating and exploring the concept of extended metric known as the Strong Altering JS-metric, a stronger version of the Altering JS-metric. The interrelation of Strong Altering JS-metric with the b-metric and dislocated metric has been analyzed and some examples have been provided. Certain theorems on fixed points for expansive self-mappings in the setting of complete Strong Altering JS-metric space have also been discussed.

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe