تعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه

This study proposes a new version of the Autoregressive Integrated Moving Average (ARIMA) model using Artificial Neural Networks (ANNs) denoted by ARIMA-NN. The new model incorporates a multi-layer perceptron with matrix multiplication within a feed-forward network. The logistic, hyperbolic tangent (tanh), and sigmoid activation functions are used for weight updates in ARIMA-NN. A new forecasting algorithm is proposed, and one-step and multiple-steps forecasting procedures are rigorously analyzed. The proposed model was evaluated against existing forecasting model using performance metrics such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (

The Zubair reservoir in the Abu-Amood field is considered a shaly sand reservoir in the south of Iraq. The geological model is created for identifying the facies, distributing the petrophysical properties and estimating the volume of hydrocarbon in place. When the data processing by Interactive Petrophysics (IP) software is completed and estimated the permeability reservoir by using the hydraulic unit method then, three main steps are applied to build the geological model, begins with creating a structural, facies and property models. five zones the reservoirs were divided (three reservoir units and two cap rocks) depending on the variation of petrophysical properties (porosity and permeability) that results from IP software interpr

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Abstract:

                    This research aims to apply the Performance Focused Activity Based Costing System in the consultant office of Al-Khwarizmi College of Engineering at the University of Technology for the purpose of measuring the cost of consulting services provided by these offices in order to reduce costs and their reflection in achieving profits. For the purpose of calculating costs accurately, and to test the hypothesis of the research, the research was applied in the office of the consultant of the College of Engineering Al-Khwarizm - University of Baghdad through the financial statement

Profit is a goal sought by all banks because it brings them income and guarantees them survival and continuity, and on the other hand, facing commitments without financial crisis. Hence the idea of research in his quest to build scientific tools and means that can help bank management in particular, investors, lenders and others to predict financial failure and to detect early financial failures. The research has produced a number of conclusions, the most important of which is that all Islamic banks sample a safe case of financial failure under the Altman model, while according to the Springate model all Islamic banks sample a search for a financial failure except the Islamic Bank of Noor Iraq for Investment and Finance )BINI(. A

Two molecular imprinted polymer (MIP) membranes for Levofloxacin (LEV) were prepared based on PVC matrix. The imprinted polymers were prepared by polymerization of styrene (STY) as monomer, N,N methylene di acrylamide as a cross linker ,benzoyl peroxide (BPO) as an initiator and levofloxacin as a template. Di methyl adepate (DMA) and acetophenone (AOPH) were used as plasticizers , the molecular imprinted membranes and the non molecular imprinted membranes were prepared.  The slopes and detection limits of the liquid electrodes ranged from -21.96 – -19.38 mV/decade and 2×10^-4M- 4×10^-4M, and Its response time was around 1 minute, respectively. The liquid  electrodes were packed with 0.1 M standar

This paper aimed to investigate the effect of the height-to-length ratio of unreinforced masonry (URM) walls when loaded by a vertical load. The finite element (FE) method was implemented for modeling and analysis of URM wall. In this paper, ABAQUS, FE software with implicit solver was used to model and analysis URM walls subjected to a vertical load. In order to ensure the validity of Detailed Micro Model (DMM) in predicting the behavior of URM walls under vertical load, the results of the proposed model are compared with experimental results. Load-displacement relationship of the proposed numerical model is found of a good agreement with that of the published experimental results. Evidence shows that load-displacement curve obtained fro