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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Permeability Prediction for Nahr-Umr Reservoir / Subba field by Using FZI Method
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 The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun May 30 2021
Journal Name
Gsc Biological And Pharmaceutical Sciences
Revision of some trematodes (Plagiorchiida: Microphallidae) from different birds in Iraq
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The adult worms of the Microphallidae family are mainly found as intestinal parasites of birds and mammals, while metacercariae is most commonly found in decapodal crustaceans. The Microphallidaeare family is spread throughout the world. It includes approximately 47 genera. Mature worms usually enter the digestive system of vertebrates, especially birds and mammals. Microphallidae contain eight subfamilies: Androcotylinae - Basantisiinae - Endocotylinae - Gynaecotylinae - Levinseniellinae - MaritrematinaeMicrophallinae - Sphairiotrematinae. Therefore, due to the lack of studies on the Microphallidae family in Iraq, we began to develop a database on this important family.

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Numerical Simulation of Flow in Rectangular Duct with Different Obstruction Heights
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       In this study, a simulation model inside a channel of rectangular section with high of (0.16 m) containing two rectangular obstruction plates were aligned variable heights normal to the direction of flow, use six model of the obstructions height of (0.059, 0.066, 0.073, 0.08 and 0.087 m) were compared with the flow behavior of the same duct without obstructions. To predict the velocity profile, pressure distribution, pressure coefficient and turbulence kinetic energy flow of air, the differential equations which describe the flow were approximated by the finite volumes method for two dimensional, by using commercial software package (FLUENT) with standard of k-ε model two dimensions turbulence flow.

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Publication Date
Fri Dec 11 2020
Journal Name
2020 Ieee 8th Conference On Systems, Process And Control (icspc)
A Survey of Different DC Faults in a Solar Power System
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Publication Date
Wed May 01 2024
Journal Name
Tropical Journal Of Pharmaceutical Research
Validation of UV-visible spectrophotometric method for niclosamide in different media
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Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit

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Publication Date
Sat Dec 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Comparative evaluation of the radiographic density of GuttaFlow® 2 in different obturation techniques using Spiral Computed Tomography
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Background: Ideal root canal obturation depends on many factors; one of them is good sealing of root canal without pores. The aim of this study was to determine the radiographic density of GuttaFlow® 2 with different obturation techniques using spiral computed tomography. Materials and Methods: Forty palatal roots of permanent maxillary first molar were used in this study. Following working length determination, root canal was prepared using rotary PROTAPER universal system. They were randomly divided into four groups of 10 roots each, the groups are Conventional lateral condensation with Apexit Plus sealer, Conventional lateral condensation with GuttaFlow® 2 as a sealer, Soft Core Regular with GuttaFlow® 2 as a sealer and singl

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