Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

This research aimed to examine the effect of concentration of dyes stuff, contact time, temperature and ratio of adsorbent weight in (gm) to volume of solution in (ml) on the percentage removal. Two dyes were used; direct blue 6 and direct yellow and the adsorbent was the maize cob. Batch experiments were performed by contacting different weights of adsorbent with 50 ml of solution of desired concentration with continuous stirring at various temperatures. The percentage of removal was calculated and the maximum percentage of removal was 80%. And as the concentration of solution, contact time, temperature and the ratio of adsorbent to volume of solution increase the percentage of removal increase.

Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

Five rice (Oryza sativa L.) cultivars (N22, Amber, Moroberekan, Kinandang Patong, and Azucena) underwent path coefficient analysis across three plant spacings (15 cm × 15 cm, 20 cm × 20 cm, and 25 cm× 25 cm) in the summer of 2017 at the College of Agricultural Engineering Sciences, University of Baghdad, Al-Jadriya, Iraq. The experiment proceeded in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. The main plots included three planting distances, and the subplot comprised five varieties. The traits studied were plant height, flag leaf area, number of tillers, panicle number, length and branches, grains per panicle, 1000-grain weight, and the percentage of unfilled grains. The results

This paper is devoted to investigate the effect of burning by fire flame on the behavior and load carrying capacity of rectangular reinforced concrete rigid beams. Reduced scale beam models (which are believed to resemble as much as possible field conditions) were suggested. Five end restrained beam specimens were cast and tested. The specimens were subjected to fire flame temperatures ranging from (25-750) ºC at age of 60 days, two temperature levels of 400ºC and 750ºC were chosen with exposure duration of 1.5 hour. The cast rectangular reinforced concretebeam (2250×375×375 mm) (length× width× height respectively) were subjected to fire. Results indicate remarkable reduction in the ultrasonic pulse velocity and rebound number of

This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.

The study aims to evaluate the removal of sulfur content from Iraqi light naphtha produced in Al-Dora refinery by adsorption desulfurization DS technique using modified activated carbon MAC loaded with nickel Ni and copper Cu as single binary metals. The experiments were carried in a batch unit with various operating parameters;  MAC dosage, agitation speed, and a contact time of 300 min at constant initial sulfur concentration 155 ppm and temperature. The results showed higher DS% by AC/Ni-Cu (66.45)% at 500 rpm and 1 g dosage than DS (29.03)% by activated carbon AC, increasing MAC dosage, agitation speed, and contact time led to increasing DS% values.  The adsorption capacity of MAC results was recorded (16,