Institutions and companies are looking to reduce spending on buildings and services according to scientific methods, provided they reach the same purpose but at a lower cost. On this basis, this paper proposes a model to measure and reduce maintenance costs in one of the public sector institutions in Iraq by using performance indicators that fit the nature of the work of this institution and the available data. The paper relied on studying the nature of the institution’s work in the maintenance field and looking at the type of data available to know the type and number of appropriate indicators to create the model. Maintenance data were collected for the previous six years by reviewing the maintenance and financial dep

Sustainability is providing the needs without compromising the ability of the strategical forming to meet their requirements. The production of warm asphalt mixtures using recycled pavements produces economic and environmentally friendly mixtures, which is the most important advantage of this work. This research aims to determine the effect of recycled asphalt concrete (RAP) on the indirect tensile strength of warm asphalt mixtures and Marshall Properties. Models of warm asphalt mixtures using Aggregate from the Al-Nibaay quarry, Asphalt with a degree of penetration (40-50) from the refinery of the cycle, and obtained Recycled asphalt concrete from Salah Al-Din Road, Al-Ameriya area in Baghdad are prepared. Use five rati

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

Abstract
A two electrode immersion electrostatic lens used in the design
of an electron gun, with small aberration, has been designed using
the finite element method (FEM). By choosing the appropriate
geometrical shape of there electrodes the potential V(r,z) and the
axial potential distribution have been computed using the FEM to
solve Laplace's equation.
The trajectory of the electron beam and the optical properties of
this lens combination of electrodes have been computed under
different magnification conditions (Zero and infinite magnification
conditions) from studying the properties of the designed electron
gun can be supplied with Abeam current of 5.7*10-6 A , electron
gun with half acceptance

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact t

The main objective and primary concern to every investor not only to achieve a greater return on his or her investments, but also to create the largest possible value of these investments the, researchers and those interested in the field of investment and financial analysis  try to develop standards  for performance      valuation      is guided through the                                     &nbsp