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Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
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The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as Exponential Model, Weibull Model, Log-logistic Model. Our research aims to adopt some of the Bayesian Optimal Criteria in achieving optimal design to estimate the optimal survival time for patients with myocardial infarction by constructing a parametric survival model based on the probability distribution of the survival times of myocardial infarction patients, which is among the most serious diseases that  threaten human life and the main cause of death all over the world, as the duration of survival of patients with myocardial infarction varies with the factor or factors causing the injury, there are many factors that lead to the disease such as diabetes, high blood pressure, high cholesterol, psychological pressure and obesity. Therefore, the need to estimate the optimal survival time was expressed by constructing a model of the relationship between the factors leading to the disease and the patient survival time, and we found that the optimal rate of survival time is 18 days.

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems
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Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real outp

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Publication Date
Mon Dec 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Optimal Corrosion Inhibition of Aluminum in 0.1M NaCl Solution
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Publication Date
Fri Dec 06 2019
Journal Name
Ssociation Of Arab Universities Journal Of Engineering Sciences
Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

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Publication Date
Thu Dec 31 2020
Journal Name
College Of Islamic Sciences
(Generalized Anxiety Disorder among Students of Baisc Education in Unv of Sulamina)
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The current research aims to measure Generalized Anxiety Disorder among students of the University of Sulaymaniyah / College of Basic Education, and to identify the significance of differences between sex, scientific specialization and age, and for that reason, the research sample of (102) male and female students was chosen in a random manner, and the researcher used the diagnostic criteria for the generalized anxiety disorder contained He mentioned it in the Statistical and Diagnostic Manual of Psychiatry, and the paragraphs of the scale were formulated according to those standards after they verify the conditions of honesty and consistency, and the use of appropriate statistical means. The results of the research indicated that genera

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Numerical Approach of Linear Volterra Integro-Differential Equations Using Generalized Spline Functions
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This paper is dealing with non-polynomial spline functions "generalized spline" to find the approximate solution of linear Volterra integro-differential equations of the second kind and extension of this work to solve system of linear Volterra integro-differential equations. The performance of generalized spline functions are illustrated in test examples

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Publication Date
Wed Dec 23 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review
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Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Wed Dec 01 2021
Journal Name
Computers &amp; Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Science And Research (ij
Mathematical Models for Predicting of Organic and Inorganic Pollutants in Diyala River Using AnalysisNeural Network
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Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Dumping and Its Challenges in Extent of World Trade Organization "Models for selected Agricultural Goods"
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The subject of dumping is considering today one of the subjects in which form an obstruction arise in front of the cycle of growth for some countries , such as the study of dumping is capturing a large attention by the competent because either a big  role and effect in growing the economies of nations then the subject of dumping became a field turn around its sides many measures and laws … and may be done resorting to by many states of the world to anti-dumping as approach of determent weapon delimit  the impact of dumping and gives the national agriculture sector the opportunity for rising and growing so this section of international economics is capturing a special importance and represent in same time an important

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