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bsj-4906
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obtained rules from positive association rules and negative association rules strengthens to each other with a pretty good confidence score.

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Publication Date
Tue Nov 17 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Correlation Study of Aromatase, Some Sex Hormones, and Body Mass Index Among Iraqi Patients with Polycystic Ovary Syndrome
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Publication Date
Thu Jun 25 2020
Journal Name
Journal Of Nusantara Studies (jonus)
POWER AND SOLIDARITY IN POSITIVE FACEBOOK POSTINGS AMIDST COVID-19 IN MALAYSIA
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Background and Purpose: Coronavirus has posed an unfamiliar threat to the world. Despite such circumstances, Malaysians continue to stay optimistic by keeping abreast with updates and mostly by seeking refuge in hopeful and consoling messages shared by fellow citizens. This study identified Facebook postings with positive messages, posted by Malaysians during the Movement Control Order (MCO) implemented by the Malaysian government as a form of prosocial behaviour.   Methodology: Through an analytic framework consisting of Positive Discourse Analysis and Critical Discourse Analysis, 15 Facebook postings related to COVID-19 were selected and identified as positive discourse, which were coded and categorised using a thematic analysi

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Modification of Irisin Level in Overweight/Obese Women during Pregnancy and Its Association with Some Metabolic Risk Factors
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Irisin is a novel myokine and adipokine, its role during pregnancy and its association with some metabolic risk factors especially pre-pregnancy body mass index (pre-BMI) need more evaluation. The aim of the study is to find whether the pre-BMI could predict irisin levels during normal pregnancy and to clarify associations of irisin with some pathological parameters.

Irisin levels were estimated by ELISA in sera of 59 normal pregnant women who enrolled from December 2016 to May 2017 at Maternity Hospital, Zakho city, Kurdistan region (Iraq). Thirty-two normal-weight pregnant (pre-BMI≤24.9 kg/m2, Age=24.03 mean±3.7standard deviation) and 27 overweight/obese-pregnant (pre-BMI>25 kg/m2, Age=27.6 mean±3.9

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Publication Date
Tue Jan 01 2019
Journal Name
Molecular Biology Research Communications
Association study of two single nucleotide polymorphisms rs10757278 and rs1333049 with atherosclerosis, a case-control study from Iraq
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Publication Date
Tue Feb 17 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An Impairment of Salivary Gland Function in Rheumatoid Arthritis: Association with Change in Salivary Biomarkers and Disease Activity
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Background: Rheumatoid arthritis is a chronic inflammatory autoimmune disease characterized by joint inflammation, involvement of exocrine salivary and lacrimal glands may occur as extra-articular mani¬festations in this disease. This study aimed to provide evidence of altered in function and composition of salivary gland in patients with rheumatoid arthritis by determine salivary flow rate and some biochemical parameters(total protein, amylase, peroxidase) and to investigate the relationship between disease activity and changes in function and composition of salivary gland. Materials and Methods: Fifty five patients with RA (7 males and 48 females) were enrolled in this study with age range (20-69) years. The patients were separated int

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Publication Date
Mon Dec 02 2024
Journal Name
Iranian Society Of Parasitology
Single Nucleotide Polymorphism of IL-18 (Rs 1946519) in Recurrent Aborted Iraqi Women and Its Association with Toxoplasmosis
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Publication Date
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Relationship Analysis Between Monetary Policy and Financial Sustainability in Iraq For the Period 2015–2021
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This research aims to study and analyze the reality of monetary policy and financial sustainability in Iraq through either a descriptive or analytical approach by trying to link and coordinate between monetary policy and fiscal policy to enhance economic sustainability. The research is based on the hypothesis that the monetary policy of Iraq contributes to achieving financial stability, which improves economic sustainability by providing aid and assistance to the state to reduce the budget deficit and exacerbate indebtedness. The author used the monetary policy indicators, the re-deduction of Treasury transfers by the central bank and the money supply, and financial sustainability indicators, including the public debt indicators and the

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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Agricultural Sciences
CORRELATION OF TMPRSS2-ERG GENE FUSION STATUS WITH CLINICOPATHOLOGICAL CHARACTERISTICS IN PROSTATE CANCER OF IRAQI PATIENTS
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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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