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A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential application in more realistic noise environments. Therefore, finding a feasible and accurate handwritten numeral recognition method that is accurate in the more practical noisy environment is crucial. To this end, this paper proposes a new scheme for handwritten numeral recognition using Hybrid orthogonal polynomials. Gradient and smoothed features are extracted using the hybrid orthogonal polynomial. To reduce the complexity of feature extraction, the embedded image kernel technique has been adopted. In addition, support vector machine is used to classify the extracted features for the different numerals. The proposed scheme is evaluated under three different numeral recognition datasets: Roman, Arabic, and Devanagari. We compare the accuracy of the proposed numeral recognition method with the accuracy achieved by the state-of-the-art recognition methods. In addition, we compare the proposed method with the most updated method of a convolutional neural network. The results show that the proposed method achieves almost the highest recognition accuracy in comparison with the existing recognition methods in all the scenarios considered. Importantly, the results demonstrate that the proposed method is robust against the noise distortion and outperforms the convolutional neural network considerably, which signifies the feasibility and the effectiveness of the proposed approach in comparison to the state-of-the-art recognition methods under both clean noise and more realistic noise environments.

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Impact of Vitamin D Status on Pregnant Women and Their Neonates: A Cross-Sectional Study
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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
The Linguistic and Conceptual Equivalence of Conner’s Revised Scales When Applied on a Sudanese Sample
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This study investigates the Linguistic and Conceptual equivalence of Conner’s Revised Scales when applied on a Sudanese sample. Sudanese parents and teachers completed behavior-rating scales on a stratified sample of 200 children. These instruments were based on Conner’s parent -48 and teacher-28 questionnaires. Following a reliable translation into Sudanese Arabic the test-retest reliability of the items and the internal consistency of the original Conner’s' revised scales were explored. The associations between scale scores and between parents and teachers scores were also examined. Both instruments displayed good reliability and the original Conners scales had satisfactory internal consistency. The inter-correlation sugg

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of The College Of Languages (jcl)
A Contrastive Study on the Syntactic Structure of Standard English and Standard Arabic Determiner Phrase
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The determiner phrase is a syntactic category that appears inside the noun phrase and makes it definite or indefinite or quantifies it. The present study has found wide parametric differences between the English and Arabic determiner phrases in terms of the inflectional features, the syntactic distribution of determiners and the word order of the determiner phrase itself. In English, the determiner phrase generally precedes the head noun or its premodifying adjectival phrase, with very few exceptions where some determiners may appear after the head noun. In Arabic, parts of the determiner phrase precede the head noun and parts of it must appear after the head noun or after its postmodifying adjectival phrase creating a discontinu

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Publication Date
Sun Jun 03 2018
Journal Name
Baghdad Science Journal
Gene Expression and Polymorphism of Interleukin-4 in a Sample of Iraqi Rheumatoid Arthritis Patients
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It was aimed to understand the interleukin-4 (IL-4) role in etio-pathogenesis of rheumatoid arthritis (RA). Two approaches were adopted. In the first one, a quantitative expression of IL4 gene was assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and such findings were correlated with some demographic, clinical and laboratory parameters, which included gender, duration of disease, disease activity score (DAS-28), rheumatoid factors (RFs), C-reactive protein (CRP) and anti-cyclic citrullinated peptide (ACCP) antibodies. In the second approach, a single nucleotide polymorphism (SNP) of IL4 gene (rs2243250) was inspected by DNA sequencing using specific primers. Fifty-one Iraqi RA patients (22 males and 29 fem

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Study on Viral Infection and Related Parameters in A Sample of Diabetes Mellitus Type 2
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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Testing of a Potentially Used Antiseptic Consists of Povidon Iodine, Hydrogen Peroxide and Aloe Vera
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In this study a new antiseptic was formulated and tested to match the effectiveness against microorganisms. The formulation consisted of Povidone - Iodine (PVP-I) (10%), H2O2 (3%) and Aloe Vera gel (pure). Different ratios of these materials were prepared within the acceptable range of pH for an antiseptic (3-6). The prepared samples were tested. The In Vitro test was performed by using four bacteria, two were Gram-Positive (Staphylococcus aureus and Bacillus cereus) and two were Gram-Negative (Escherichia coli and Pseudomonas aeruginosa). The new antiseptic showed 100% killing rate for E. coli, Ps. aeruginosa and S. aureus and 96.4667% killing rate for B. cereus. When the new antiseptic was compared with two common

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Publication Date
Thu May 28 2020
Journal Name
Journal Of Generic Medicines: The Business Journal For The Generic Medicines Sector
Determinants of national drug products acceptance across patients, pharmacists, and manufacturers: A mixed method study
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Introduction

The national pharmaceutical industry is pivotal for both the health sector and the national economy. This study aims to identify determinants of national drug products acceptance. The objectives of this study were to quantitatively measure the level of patient and community pharmacist acceptance of national drug products available in community pharmacies and to qualitatively explore the barriers facing national pharmaceutical companies and investigate the suggested solutions.

Methods

This cross-sectional study used an explanatory mixed method design. It was conducted in Baghdad, Iraq from July through October 2018. The stud

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Estimation of Water and Energy Saving by Rainwater Harvesting: Sulaimani City as a Case Study
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Rainwater harvesting could be a possible solution to decrease the consequences of water scarcity and energy deficiency in Iraq and the Kurdistan Region of Iraq (KRI). This study aims to calculate the water and energy (electricity) saved by rainwater harvesting for rooftops and green areas in Sulaimani city, KR, Iraq. Various data were acquired from different formal entities in Sulaimani city. Moreover, Google Earth and ArcMap 10.4 software were used for digitizing and calculating the total rooftop and green areas. The results showed that for the used runoff coefficients (0.8 and 0.95), the harvested rainwater volumes were 2901563 and 12197131 m³ during the study period (2005 – 2006) and (2019-2020). Moreover, by compa

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