The economy of a city has an important role not only in its establishment but also in its development. This is quite clear in the city of Baghdad throughout its history since its building in 762 A.D. In addition, most of its problems that the city is suffering from are basically related to not giving enough importance to the economic factors in the master planning of Baghdad since 1950’s. This may explain the failiars of master plans in dealing with the actual population growth and the city's inability to absorb such increases and interrelated and diverse activities which are negatively reflected on the economic variables particularly the effect on the land values, and the strong competitions amongst the land uses without previ

The international system that established the United Nations after the end of the Second World War witnessed many changes. These changes overshadowed the nature of the work of the international organization, especially its first and most important executive organ (the Security Council). This has sometimes weakened and dulled the Security Council's role in performing the tasks stipulated in the Charter of the Organization, which has led the Organization itself to work on reforms within it in general and to seek reforms in the Security Council in particular. Academic and advisory efforts were made to submit proposals for amendment to be reflected on the Council's performance effectiveness.

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

The accurate determination of nuclear radius is fundamental to understanding nuclear structure and interactions. The present study conducts a comprehensive theoretical analysis of nuclear radius measurements using various nuclear structure models, including the empirical mass-number scaling model, the Hartree-Fock approach, and the relativistic mean-field (RMF) theory. These models are systematically compared against experimental nuclear radii to evaluate their predictive accuracy and assess their strengths and limitations. The study also incorporates an uncertainty analysis to quantify the reliability of theoretical predictions, employing Monte Carlo simulations and Bayesian inference techniques to refine estimations. The results r

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

Objectives: to evaluate patient knowledge with hemodialysis and to determine the effectiveness of Self-regulation Fluid Program on Patients with hemodialysis self-efficacy for fluid adherence in Al-Diwaniyah Teaching Hospital.

Methodology: A quasi-experimental design (two group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from (15^th of October 2018 to 20^th of May 2019) on a non-probability (purposive) sample consisting of (60 patients) treatment in hemodialysis units. A questionnaire was built as a data collection tool and consisted of four parts:

First part: Demographic characteristics of the pati

In aired and semiarid areas like Iraq, saline soil may be considered one of the major concerns. In addition to environmental effects, they may produce significant geotechnical hazards that could interrupt the structure stability depending on the salt type and its concentration. So, it is crucial to identify the degree of the soil salinity with a proper tool for getting a qualified assessment and consequently offering a suitable treatment. In this paper, the electrical resistivity technique has been employed to detect the degree of soil salinity by considering a new electronic system. The system used a single-phase Direct Current (DC) to Alternating Current (AC) inverter accompanied by a transformer. Natural soils became artificially saline

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s