High-sensitive cardiac troponin I (hs-cTnI) is a recognized marker of myocardial injury in acute coronary syndromes, but its utility in chronic coronary syndromes (CCS) remains unclear. Midkine (MK), a heparin-binding growth factor, plays a role in inflammation and vascular remodeling in atherosclerosis. This cross-sectional study aimed to evaluate the predictive value of serum hs-cTnI and MK in determining the severity of coronary artery obstruction in patients with CCS. The study included 125 subjects undergoing coronary angiography (CAG) at the Iraqi Center of Heart Disease/ Medical City/Baghdad, from March to December 2024. Subjects were classified into three groups based on CAG findings: no CAD, 1- or 2-vessel disease, and 3-ve

Spatial data analysis is performed in order to remove the skewness, a measure of the asymmetry of the probablitiy distribution. It also improve the normality, a key concept of statistics from the concept of normal distribution “bell shape”, of the properties like improving the normality porosity, permeability and saturation which can be are visualized by using histograms. Three steps of spatial analysis are involved here; exploratory data analysis, variogram analysis and finally distributing the properties by using geostatistical algorithms for the properties. Mishrif Formation (unit MB1) in Nasiriya Oil Field was chosen to analyze and model the data for the first eight wells. The field is an anticline structure with northwest- south

B Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2

This paper compares between the direct and indirect georeferencing techniques in Photogrammetry bases on a simulation model. A flight plan is designed which consists of three strips with nine overlapped images for each strip by a (Canon 500D) digital camera with a resolution of 15 Mega Pixels.

The triangulation computations are carried out by using (ERDAS LPS) software, and the direct measurements are taken directly on the simulated model to substitute using GPS/INS in real case. Two computational tests have been implemented to evaluate the positional accuracy for the whole model and the Root Mean Square Error (RMSE) relating to (30) check points show that th

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen