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A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve Bayesian classifier (NBC) have been enhanced as compared to the dataset before applying the proposed method. Moreover, the results indicated that issa was performed better than the statistical imputation techniques such as deleting the samples with missing values, replacing the missing values with zeros, mean, or random values.

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Association Of Arab Universities For Basic And Applied Sciences
Semi-analytical method for solving Fokker-Planck’s equations
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Publication Date
Wed Mar 01 2017
Journal Name
جامعة كرميان
The effect of a training program for chemistry teachers based on the strategy of both sides of the brain together on the thinking patterns of their students
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Publication Date
Tue Jul 01 2014
Journal Name
Ieee Transactions On Circuits And Systems I: Regular Papers
Crosstalk-Aware Multiple Error Detection Scheme Based on Two-Dimensional Parities for Energy Efficient Network on Chip
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Achieving reliable operation under the influence of deep-submicrometer noise sources including crosstalk noise at low voltage operation is a major challenge for network on chip links. In this paper, we propose a coding scheme that simultaneously addresses crosstalk effects on signal delay and detects up to seven random errors through wire duplication and simple parity checks calculated over the rows and columns of the two-dimensional data. This high error detection capability enables the reduction of operating voltage on the wire leading to energy saving. The results show that the proposed scheme reduces the energy consumption up to 53% as compared to other schemes at iso-reliability performance despite the increase in the overhead number o

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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Laser
Plasmonic Nanoparticles Decorated Salty Paper Based on SERS Platform for Diagnostic low-Level Contamination: Lab on Paper
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In this research, a low cost, portable, disposable, environment friendly and an easy to use lab-on-paper platform sensor was made. The sensor was constructed using a mixture of Rhodamine-6G and gold nanoparticles also Sodium chloride salt. Drop–casting method was utilized as a technique to make a platform which is a commercial office paper. A substrate was characterized using Field Emission Scanning Electron Microscope, Fourier transform infrared spectroscopy, UV-visible spectrophotometer and Raman Spectrometer. Rh-6G Raman signal was enhanced based on Surface Enhanced Raman Spectroscopy technique utilized gold nanoparticles. High Enhancement factor of Plasmonic commercial office paper reaches up to 0.9 x105 because of local surface pl

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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Spatial Data Analysis for Geostatistical Modeling of Petrophysical Properties for Mishrif Formaiton, Nasiriya Oil Field
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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

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Publication Date
Sun Apr 03 2011
Journal Name
لمؤتمر العلمي الرابع لكلية التربية/ جامعة سامراء
A comparison between alanine aminopeptidase (AAP) activity in type 2 diabetes and diabetic cardiac patients.
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Publication Date
Sat Oct 01 2016
Journal Name
2016 6th International Conference On Information Communication And Management (icicm)
Enhancing case-based reasoning retrieval using classification based on associations
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Publication Date
Thu Feb 01 2018
Journal Name
Applied Mathematical Modelling
Identification of a multi-dimensional space-dependent heat source from boundary data
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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the Current Financial Crisis : Causes and Solutions (Iraqi crisis a model , based on the public budget for the fiscal year 2016)
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The research aims to analysis of the current financial crisis in Iraq through knowing its causes and then propose some solutions that help in remedy the crisis and that on the level of expenditures and revenues, and has been relying on the Federal general budget law of the Republic of Iraq for the fiscal year 2016 to obtain the necessary data in respect of the current expenditures and revenues which necessary to achieve the objective of the research , and through the research results has been reached to a set of conclusions which the most important of them that causes of the current financial crisis in Iraq , mainly belonging to increased expenditures and especially the current ones and the lack of revenues , especially non-oil o

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