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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
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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Publication Date
Wed Jan 01 2025
Journal Name
Iraqi National Journal Of Earth Science (injes)
The Effect of Satellite Image Fusion on the Classification Process by Using Multiple Sensors
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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Exchange Rate Fluctuations on the Behavior of the Stock Markets in the Turkish Economy
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             A discussion about the repercussions of the exchange rate on the behavior of stock markets became one of the basic principles of financial economics. The Istanbul Stock Exchange , considered  one of the fastest financial markets growing in the region, driven by solid economic activity, for a diversified economy  which classified as one of the the fastest growing economies in the world. However, the aforementioned market witnessed sharp fluctuations in the past few months, coinciding with the continuous fluctuations in the exchange rate of the Turkish lira, posing a serious challenge to the economic and investment environment in a c

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Working Memory Classification Enhancement of EEG Activity in Dementia: A Comparative Study
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The purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the  classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Reducing Organizational Anomie in Light of Entrepreneurial Behavior
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The research aims to clarify the role of the main variable represented by the four dimensions of entrepreneurial behavior (creative, risk-taking, seizing opportunities, proactivity), in Reducing the dependent variable of organizational anomie with the dimensions (Organizational Normlessness, Organizational Cynicism, Organizational Valuelessness).

The experimental, analytical method was adopted in the completion of the research, and an intentional sample of (162) individuals in the administrative levels (higher and middle) in the factory was taken. The questionnaire was also adopted as the main tool, which

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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of Educational And Psychological Researches
Translation & Adaptation of(Patterns) & (Assembly) Scales of The Flanagan Aptitude Classification Tests (FACT)
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The Flanagan Aptitude Classification Tests (FACT) assesses aptitudes that are important for successful performance of particular job-related tasks. An individual's aptitude can then be matched to the job tasks. The FACT helps to determine the tasks in which a person has proficiency. Each test measures a specific skill that is important for particular occupations. The FACT battery is designed to provide measures of an individual's aptitude for each of 16 job elements.

The FACT consists of 16 tests used to measure aptitudes that are important for the successful performance of many occupational tasks. The tests provide a broad basis for predicting success in various occupational fields. All are paper and pen

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Publication Date
Tue Dec 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Belief about Medications Among Type 2 Diabetic Patients Attending the National Diabetes Center in Iraq.
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Diabetes mellitus is a common health problem worldwide counting about 1.2 million cases in Iraq in 2015. Taking in account of the patient’s beliefs about the prescribed medication had been reported to be one of the most important factors that affects adherence where holding positive beliefs about medications is a prerequisite for intentional adherence. The aim of the current study was to investigate and assess beliefs about medicines among type 2 diabetic patients and to determine possible association between this belief and glycemic control as well as some patient-specific factors. This study is a cross-sectional study carried out on 380 (mean age 56.58± 10.06 years) already diagnosed T2DM patients who attended the National Diabetes

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
A Comparative Study on Association Rule Mining Algorithms on the Hospital Infection Control Dataset
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Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Study of Adhesion Molecules in Diabetes Mellitus Type2 Iraqi Patients with Dyslipidemia
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Background: Cell adhesion molecules are protein entities that are located on the cell surface. The vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) expression is related to type 2 diabetes mellitus (T2DM) with dyslipidemia. Objectives: To determine the levels of VCAM-1 and ICAM-1 in T2DM patients with dyslipidemia and to explore the relationship between VCAM-1 and ICAM-1 and the development of dyslipidemia in T2DM patients. Patients and methods: The study included 150 individuals with an age range of (35-55) years. Patients with diabetes for more than 5 years were excluded. Fifty healthy individuals constituted Group 1 (G1), fifty patients with T2DM constituted Group 2 (G2), and fifty T2DM p

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