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Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Correlation for fitting multicomponent vapor-liquid equilibria data and prediction of azeotropic behavior
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Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –

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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Theoretical Prediction of Optimum Chilled Water Distribution Configuration in Air Conditioning Terminal Unit
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 The distribution of chilled water flow rate in terminal unit is a major factor used to evaluate the performance of central air conditioning unit. In this work, a theoretical chilled water distribution in the terminal units has been studied to predict the optimum heat performance of terminal unit. The central Air-conditioning unit model consists of cooling/ heating coil (three units), chilled water source (chiller), three-way and two-way valve with bypass, piping network, and pump. The term of optimization in terminal unit ingredient has two categories, the first is the uniform of the water flow rate representing in statically permanents standard deviation (minimum value) and the second category is the maximum heat transfer rate fro

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Wed Sep 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Effective Bed Thermal Conductivity and Heat Transfer Coefficient in Fluidized Beds
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Experimental study of heat transfer coefficients in air-liquid-solid fluidized beds were carried out by measuring the heat rate and the overall temperature differences across the heater at different operating conditions. The experiments were carried out in Q.V.F. glass column of 0.22 m inside diameter and 2.25 m height with an axially mounted cylindrical heater of 0.0367 m diameter and 0.5 m height. The fluidizing media were water as a continuous phase and air as a dispersed phase. Low density (Ploymethyl-methacrylate, 3.17 mm size) and high density (Glass beads, 2.31 mm size) particles were used as solid phase. The bed temperature profiles were measured axially and radially in the bed for different positions. Thermocouples were connecte

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Efficiency Prediction and Performance Characterization of Photovoltaic Solar Panel at Baghdad Climate Conditions
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The performance of a solar cell under sun radiation is necessary to describe the electrical parameters of the cell. The Prova 200 solar panel analyzer is used for the professional testing of four solar cells at Baghdad climate conditions. Voltage -current characteristics of different area solar cells operated under solar irradiation for testing their quality and determining the optimal operational parameters for maximum electrical output were obtained. A correlation is developed between solar cell efficiency h and the corresponding solar cell parameters; solar irradiance G, maximum power Pmax, and production date P. The average absolute error of the proposed correlation is 5.5% for 40 data points. The results also show th

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Fri May 01 2026
Journal Name
Civil Engineering Journal
Bearing Capacity Enhancement of Hexagonal Skirted Footings: Numerical, Regression, and ANN-Based Prediction
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This paper presents a comprehensive numerical analysis of the improvement in bearing capacity and settlement performance of hexagonal shallow footings with inclined skirts. Various numerical analyses were conducted using PLAXIS 3D to investigate the influence of skirt length-to-footing width (L/B) ratios and skirt inclination angles (θ) on hexagonal footings in loose sand. The models showed very good agreement with experimental data reported in previous studies, with an R² value of 0.996 and a maximum error of less than 4.31%. It was concluded that the inclusion of inclined skirts has a positive effect on bearing capacity, increasing it by up to approximately 2.97 times compared to non-inclined configurations, while significantly

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Publication Date
Sat Jun 01 2024
Journal Name
Nasaq Journal
The Value of Collaborative Learning in Developing Student's Listening Skills
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Social interaction is the platform that enables people to connect and practice language. Active listening stimulates them to understand the language they are speaking. The problem of the study highlights that less attention to listening among speaking, reading, and writing skills causes the weakness of collaborative learning. This paper contributes to characterizing the effectiveness of collaborative learning in developing learner’s listening skills. It aims to underscore the role of target language learners as members of the learning groups and of the teacher in the collaborative learning process. 130 Iraqi EFL teachers from different colleges at the University of Baghdad participated in this study. The scores in the statistical data wer

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Publication Date
Mon Dec 25 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessing Quality of Life Among Patients with Diabetes Mellitus, Hypertension or Both Diseases in Al-Najaf Province /Iraq
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this study deals with effect of diabetes and hypertension on quality of life

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