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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
Mon Mar 09 2020
Journal Name
Agrosystems, Geosciences & Environment
In-season potato yield prediction with active optical sensors
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Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analyzing the effect of labor productivity and capital on manufacturing industries in Iraq and some Arab countries for the period 1990-2000
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يلعب القطاع الصناعي التحويلي في أي قطر دوراً هاماً في تحقيق التنمية الصناعية، اذ تتحد تاثيراته فيها على طبيعة الدور المرسوم له وعلى مدى فاعلية هذا القطاع الحيوي الذي يعد اتجاه نحو التعاظم المضطرد لمستويات الانتاجية " Levels of productivity"والتنويع الانتاجي والتدفق المستمر للتجديد التكنولوجي من اهم دلائله.

ويعد مؤشر الانتاجية بصفة عامة وانتاجيتي العمل وراس المال بصفة خاصة من الم

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Publication Date
Wed Mar 02 2022
Journal Name
Remittances Review
Analyzing the Influence of Information and Communication Technologies (ICT) on the Per Capita GDP of Iraq from 2004 to 2021
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The study aims to identify the theoretical literature for all the variables of the study (ICT, GDP) as well as to identify the practical side of the impact of ICT on the per capita GDP in Iraq for the period (2004-2021). The study was based on the hypothesis that ICT impacts per capita GDP in Iraq. The problem of the study was to answer the question: does ICT contribute to per capita GDP? The study concluded that an increase in the rate of internet users per 100 people by one unit would increase. Increasing the landline telephone rate per 100 people by one unit will increase GDP per capita. In addition, increasing the mobile phone rate per 100 people by one unit will increase GDP per capita. The study recommended adopting rational poli

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Publication Date
Sun Mar 06 2022
Journal Name
Al–bahith Al–a'alami
Semiotic criteria for analyzing religious symbols in press reports Qantara news site as a model
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The report includes a group of symbols that are employed within a framework that gives a language of greater impact. This research discusses the problem of the semiotic employment of religious symbols in press reports published in the electronic press across two levels: Reading to perceive the visual message in its abstract form, and the second for re-understanding and interpretation, as this level gives semantics to reveal the implicit level of media messages through a set of semiotic criteria on which it was based to cut texts to reach the process of understanding and interpretation.

The report includes a group of symbols that are employed within a framework that gives a language of greater impact. This research discusses the p

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Publication Date
Sat Feb 07 2026
Journal Name
Algorithms
An In-Depth Review of Speech Enhancement Algorithms: Classifications, Underlying Principles, Challenges, and Emerging Trends
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Speech enhancement aims to improve speech quality and intelligibility in noisy environments and is important in applications such as hearing aids, mobile communications and automatic speech recognition (ASR). This paper shows a structured review of speech enhancement techniques, classified depending on the channel configuration and signal processing framework. Both traditional and modern approaches are discussed, including classical signal processing methods, machine learning techniques, and recent deep learning-based models. Furthermore, common noise types, widely used speech datasets, and standard evaluation metrics for evaluating speech quality and intelligibility are reviewed. Key challenges such as non-stationary noise, data li

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Applied Hematology
D-dimer and Ferritin Levels in Prediction of COVID-19 Severity
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Abstract<sec> <title>BACKGROUND:

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

AIM OF THE STUDY:

The aim of the study is to demonstrate the role of COVID-19 on coagulation parameters D-dimer and ferritin with their association with COVID-19 severity and disease progression in a single-center study.

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Sun Dec 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of The Chemical Composition and Physical properties of Aged Asphalt Cement
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In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

loge(DI)=a1+0.0123(2loge T

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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