Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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

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

The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

Objective(s): To identify the relationship between demographic characteristics of patients with renal
failure and to find out the relationship between some risk factors like (family history, alcohol drinking,
smoking and chronic disease) with renal failure patients.
Methodology: Case control study design was carried out in order to achieve the objectives of the
study by using the assessment technique in Baghdad teaching hospital from March 5
th, 2017 to October
10th
, 2017, The sample was (cases & control) sample, present study include 200 cases, 100 was case
study the patient who entered in Baghdad teaching hospital, while another 100 was control study. The
data was collected by interview questionnaire inc