Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the data are challenging because they contain many outliers, non homogeneous covariance matrices across classes, exact duplicate rows that were removed before modelling, and linear correlations among certain variables. The study objective was to train and evaluate models that discriminate among the three classes and yield accurate, well calibrated predictions for future cases in similar clinical settings, but the diagnostic properties of the data limited the applicability of classical discriminant functions; therefore two supervised learners were employed: Classification and Regression Trees (CART) and Extreme Gradient Boosting (XGBoost), together with preprocessing that removed exact duplicate rows and excluded VLDL because it is algebraically derived from triglycerides in mmol per liter as VLDL equals triglycerides divided by 2.2, which would introduce redundancy and multicollinearity. On the heldout test set, XGBoost achieved higher Accuracy at 98.18 percent compared with 97.58 percent for CART and higher Balanced Accuracy at 93.84 percent compared with 88.16 percent for CART, indicating that XGBoost provided the strongest overall operating point for this three-class task while CART remains useful when simple and transparent rules are required.
This research will cover different aspects of estimating process of construction work in a desert area. The inherent difficulties which accompany the cost estimating of the construction works in desert environment in a developing country, will stem from the limited information available, resources scarcity, low level of skilled workers, the prevailing severe weather conditions and many others, which definitely don't provide a fair, reliable and accurate estimation. This study tries to present unit price to estimate the cost in preliminary phase of a project. Estimations are supported by developing mathematical equations based on the historical data of maintenance, new construction of managerial and school projects.
... Show MoreVariation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine w
... Show MoreBackground : Diabetes mellitus, also known as blood sugar, is a series of metabolic disorders described by high blood glucose levels (hyperglycemia), low blood glucose (hypoglycemia), or both, resulting from defects in insulin production, insulin action, or both. Numerous studies have shown that interleukin (IL-6) acts on skeletal muscle cells , liver cells, and pancreas cells to influence glucose balance and metabolism, which directly or indirectly contributes to the development of diabetes. Research in this area is crucial because diabetes is recognized as a major risk factor for many diseases like Diabetic retinopathy, Diabetic nephropathy, Diabetic Neuropathy , heart disease and others. Patients and methods : In this study, we
... Show MoreIraqi industrial units face strong competition due to many problems including1- high production costs2- weak interest in studying the market3- lack of government support for their products4- dumping the market with imported products with specifications and a competitive price as well as adopting the traditional cost system in calculating costs that do not provide appropriate information for pricing decisions Which requires studying and analyzing these problems and dealing with them by adopting modern technologies so that they can compete, so the research aims to show the knowledge bases of technology Activity- Based Costing, with an indication of the role of technology Activity- Based Costing in rationalizing the tax In, and the
... Show MoreThat any industrial company that must think about marketing mechanisms and who are the beneficiaries and the pursuit of gain customer satisfaction with access to competitive advantages. Most industrialized our companies from a variety of problems experienced both in the field of production, marketing, or keep up with new developments or commitment to quality standards, which caused the reluctance of customers to buy local products for various reasons, and especially in light of unplanned economic policy and exposure to market to imported products flooding the market with various goods and services that do not can the domestic industry rival, which has competitive advantages and meet business requirements, but others arrived to stop or as
... Show MoreObjective(s): To Evaluate Diabetes self –management among patients in Baghdad City and to compare
between these patients self-management relative to the type of the disease.
Methodology: A descriptive design was conducted in Baghdad city, started from November 16th 2017 to the
end of May 17 th 2018 in order to evaluate Diabetes self-management. Purposive (non-probability) sample,
which was consisted of (120) patients who were diagnosed with D.M. The sample is comprised of (60) patient
with diabetes type I and (60) patient with diabetes type II. It is consisted of (60) male and (60) female. A
questionnaire is constructed for the purpose of the study. It is composed of (42) items. Reliability and validity of
the ques
In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
The co-occurrence of metabolic syndrome with type 2 diabetes mellitus (T2DM) will potentiate the morbidity and mortality that may be associated with each case. Fasting triglycerides-glucose index (TyG index) has been recommended as a useful marker to predict metabolic syndrome. Our study aimed to introduce gender-specific cut-off values of triglycerides- glucose index for diagnosing metabolic syndrome associated with type 2 diabetes mellitus. The data were collected from Baghdad hospitals between May - December 2019. The number of eligible participants was 424. National cholesterol education program, Adult Treatment Panel III criteria were used to define metabolic syndrome. Measurement of fasting blood glucose, lipid pro
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