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New insights into porosity determination using artificial intelligence techniques for carbonate reservoirs

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Petroleum 2018年第4期4卷 408-418页

作者： Salaheldin Elkatatny Zeeshan Tariq Mohamed Mahmoud abdulazeez abdulraheem Department of Petroleum Engineering King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia Petroleum Engineering Department Cairo UniversityCairo Egypt Petroleum Engineering Department Suez UniversitySuezEgypt

The porosity of the petroleum reservoirs is considered one of the most important parameters in reserve estimation because it determines the effective volume of the hydrocarbon that is stored in the *** on the reserve estimation,the development plan can be set and *** can be determined in the laboratory which is the most expensive *** also can be determined from the logs such as density,neutron,sonic,and NMR *** are a lot of uncertainties in the porosity estimation from wireline logs because it depends on many statistical analysis and also is affected by the logging environment and logging *** prediction of the porosity from different porosity logs using artificial intelligence(AI)methods validated with the laboratory measured values is the best method to determine an accurate value of the rock *** objective of this research is to evaluate AI tools such as artificial neural network(ANN),Support vector machine(SVM)and Adaptive neuro fuzzy inference system(ANFIS)to predict the reservoir porosity based on wireline log *** than 1700 field measurements of porosity with logs data were used for training and testing the AI *** results obtained showed that ANN and ANFIS can be used to estimate the reservoir porosity based on log data with a high correlation coefficient(R)and low average absolute percentage error(AAPE).The main inputs required for porosity estimation are bulk density,neutron porosity,and sonic compressional *** developed mathematical equation based on the weights and bias of the ANN model can be used to predict the reservoir porosity based on log data with a correlation coefficient of 0.98 and an AAPE less than 8%.The advantage of this work is that we extracted the mathematical model from the ANN that can be used directly to determine the porosity without the need for training and testing the *** porosity estimation from the neutron-density crossplots,which is the current te

关键词： Porosity Artificial intelligence Neural network Carbonate reservoir Logging

The coronavirus disease 2019 (COVID-19) pandemic: A review and an update on cases in Africa

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Asian Pacific Journal of Tropical Medicine 2020年第5期13卷 199-203页

作者： abdulazeez A.Anjorin Department of Microbiology(Virology Research) Lagos State UniversityOjoLagosNigeria

The world has experienced several epidemics posing serious threat to global public health,including the 2002 severe acute respiratory syndrome(SARS)epidemic that caused 800 deaths out of about 8000 cases,the 2009 H1N1 pandemic with 18500 deaths,the 2012 Middle East respiratory syndrome(MERS)epidemic that caused 800 deaths out of 2500 cases,the 2014 Ebola outbreak with 28616 cases and 11310 deaths,and the current coronavirus disease(COVID-19)pandemic with more than 35000 deaths out of over 730000 confirmed cases till *** infectious diseases continue to infect and reduce human *** COVID-19 pandemic has spread to more than 114 countries before it was officially declared as a pandemic by the WHO on the 11th March ***,the first set of index cases inAfrica,and the differences between SARS-CoV-2 and other coronaviruses in addition to the preventive strategies on the emergence of COVID-19 were reviewed.

关键词： Coronavirus COVID-19 SARS-CoV-2 Infectious disease Africa

Hybrid Trainable System for Writer Identification of Arabic Handwriting

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Computers, Materials & Continua 2021年第9期68卷 3353-3372页

作者： Saleem Ibraheem Saleem Adnan Mohsin abdulazeez Department of Information Technology Technical Informatics College of AkreDuhok Polytechnic UniversityDuhok42004Iraq

Writer identification(WI)based on handwritten text structures is typically focused on digital characteristics,with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/*** studies have indicated that a word’s attributes contribute to greater recognition than the attributes of a character or *** a result of the complexity of Arabic handwriting,segmenting and separating letters and strokes from a script poses a challenge in addition to WI *** this work,we propose new texture features for WI based on *** histogram of oriented gradient(HOG)features are modified to extract good features on the basis of the histogram of the orientation for different angles of *** fusion of these features with the features of convolutional neural networks(CNNs)results in a good vector of powerful ***,we reduce the features by selecting the best ones using a genetic *** normalization method is used to normalize the features and feed them to an artificial neural network *** results show that the proposed augmenter enhances the results for HOG features and ResNet50,as well as the proposed model,because the amount of data is *** a large data volume helps the system to retrieve extensive information about the nature of writing *** affective result of the proposed model for whole paragraphs,lines,and sub words is obtained using different models and then compared with those of the CNN and *** whole paragraphs produce the best results in all models because they contain rich information and the model can utilize numerous features for different *** HOG and CNN features achieve 94.2%accuracy for whole paragraphs with augmentation,83.2%of accuracy for lines,and 78%accuracy for sub ***,this work provides a system that can identify writers on the basis of their handwriting and builds a powerful model that can help

关键词： Writer identification handwritten Arabic HOG features artificial neural network segmentation CNN features

A new approach for pseudo hyperbolic partial differential equations with nonLocal conditions using Laplace Adomian decomposition method

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Applied Mathematics(A Journal of Chinese Universities) 2024年第4期39卷 750-758页

作者： Mahmut Modanli Sadeq Taha abdulazeez Ahmad Muhamad Husien Department of Mathematics Harran UniversityFaculty of Arts and Sciences63300SanliurfaTurkey Department of Mathematics Duhok UniversityCollege of Basic EducationDuhokIraq Department of Mathematics Duhok UniversityCollege of ScienceDuhokIraq

This paper provides a nonlinear pseudo-hyperbolic partial differential equation with non-local *** the importance of this problem,the exact solution to this problem is rare in the ***,the Laplace-Adomian Decomposition Method(LADM)is used to provide a new approach to solving this ***,we give a comparison between the exact and approximate solutions at various points with absolute *** obtained result showed that the proposed method is effective and accurate for this problem and can be used for many other evolution of nonlinear equations in mathematical physics.

关键词： pseudo hyperbolic equations nonlocal conditions Laplace-Adomian decomposition method Approximate solutions

A New Segmentation Framework for Arabic Handwritten Text Using Machine Learning Techniques

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Computers, Materials & Continua 2021年第8期68卷 2727-2754页

作者： Saleem Ibraheem Saleem Adnan Mohsin abdulazeez Zeynep Orman Department of Information Technology Technical Informatics College of AkreDuhok Polytechnic UniversityDuhok42004Kurdistan RegionIraq Department of Computer Engineering Faculty of EngineeringIstanbul University-CerrahpasaIstanbul34320Turkey

The writer identification(WI)of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist *** is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies,including old national and religious *** this study,we proposed a new affective segmentation model by modifying an artificial neural network model and making it suitable for the binarization stage based on *** modified method is combined with a new effective rotation model to achieve an accurate segmentation through the analysis of the histogram of binary ***,propose a new framework for correct text rotation that will help us to establish a segmentation method that can facilitate the extraction of text from its *** projections and the radon transform are used and improved using machine learning based on a co-occurrence matrix to produce binary *** training stage involves taking a number of images for model *** images are selected randomly with different angles to generate four classes(0–90,90–180,180–270,and 270–360).The proposed segmentation approach achieves a high accuracy of 98.18%.The study ultimately provides two major contributions that are ranked from top to bottom according to the degree of *** proposed method can be further developed as a new application and used in the recognition of handwritten Arabic text from small documents regardless of logical combinations and sentence construction.

关键词： Writer identification handwritten Arabic biometric systems artificial neural network segmentation skew detection model

Lycopene stabilizes lipoprotein levels during D-galactosamine/lipopolysaccharide induced hepatitis in experimental rats

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Asian Pacific Journal of Tropical Biomedicine 2012年第12期2卷 975-980页

作者： Sheik abdulazeez Sheriff Thiruvengadam Devaki Department of Biochemistry University of MadrasGuindy Campus

Objective:To investigate the effect of lycopene on lipoprotein metabolism during D-galactosamine/lipopolysacchoride(D-Gal/LPS)induced hepatitis in experimentul ***:The efficacy of lycopene was validated during D-Gal/LPS induced hepatitis by analyzing the activity of lipid metabolizing enzymes such as lipoprotein lipase(LPL),lecithincholesterol acyl transferase(LCAT)and hepatic triglyceride lipase(HTCL).Lipo protein analyses were done by the estimation of very low density lipoprotein cholesterol(VLDL),low density lipoprotein cholesterol(LDL)and high density lipoprotein cholesterol(HDL).Remits:The toxic insult of D-galactosamine/lipopolysaccharide(D-Gal/LPS)in experimental group of animals reduces the normal values of lipid metabolizing enzymes due to liver *** significant drop in the levels of HDL and concomitant increase in the values of VLDL and LDL were *** pretreatment of lycopene restore these altered values to near normal level in experimental group of ***:In the light of results,it can be concluded that administration lycopene stabilizes the lipoprotein levels by regulating the lipid metabolizing enzymes through its antioxidant defense and helps to maintain the normal lipid metabolism during toxic injury in liver.

关键词： Lycopene Dyslipidemia Galactosamine Antioxidants Lipoproteins

Shape, Color and Texture Based CBIR System Using Fuzzy LogicClassifier

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Computers, Materials & Continua 2019年第6期59卷 729-739页

作者： D.Yuvaraj M.Sivaram B.Karthikeyan Jihan abdulazeez Department of Computer Science Cihan University-Duhok-42001Kurdistan Region-Iraq Department of Computer Networking Lebanese French UniversityErbil-44001Kurdistan Region-Iraq School of Computing SASTRA Deemed UniversityThanjavur-613401India

The perfect image retrieval and retrieval time are the two major challenges inCBIR systems. To improve the retrieval accuracy, the whole database is searched basedon many image characteristics such as color, shape, texture and edge information whichleads to more time consumption. This paper presents a new fuzzy based CBIR method,which utilizes colour, shape and texture attributes of the image. Fuzzy rule based systemis developed by combining color, shape, and texture feature for enhanced image *** this approach, DWT is used to pull out the texture characteristics and the region basedmoment invariant is utilized to pull out the shape features of an image. Color similarityand texture attributes are extorted using customized Color Difference Histogram (CDH).The performance evaluation based on precision and BEP measures reveals the superiorityof the proposed method over renowned obtainable approaches.

关键词： Image retrieval color histogram texture edge orientation retrieval accuracy

Multi-Level Fusion in Ultrasound for Cancer Detection Based on Uniform LBP Features

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Computers, Materials & Continua 2021年第3期66卷 3363-3382页

作者： Diyar Qader Zeebaree Adnan Mohsin abdulazeez Dilovan Asaad Zebari Habibollah Haron Haza Nuzly Abdull Hamed Research Center of Duhok Polytechnic University DuhokKurdistan RegionIraq Presidency of Duhok Polytechnic University Duhok Kurdistan RegionIraq Center of Scientific Research and Development Nawroz University DuhokKurdistan RegionIraq School of Computing University Teknologi MalaysiaJohorMalaysia

Collective improvement in the acceptable or desirable accuracy level of breast cancer image-related pattern recognition using various schemes remains *** the combination of multiple schemes to achieve superior ultrasound image pattern recognition by reducing the speckle noise,an enhanced technique is not *** purpose of this study is to introduce a features-based fusion scheme based on enhancement uniform-Local Binary Pattern(LBP)and filtered noise *** surmount the above limitations and achieve the aim of the study,a new descriptor that enhances the LBP features based on the new threshold has been *** paper proposes a multi-level fusion scheme for the auto-classification of the static ultrasound images of breast cancer,which was attained in two ***,several images were generated from a single image using the pre-processing *** andWiener filterswere utilized to lessen the speckle noise and enhance the ultrasound image *** strategy allowed the extraction of a powerful feature by reducing the overlap between the benign and malignant image ***,the fusion mechanism allowed the production of diverse features from different filtered *** feasibility of using the LBP-based texture feature to categorize the ultrasound images was *** effectiveness of the proposed scheme is tested on 250 ultrasound images comprising 100 and 150 benign and malignant images,*** proposed method achieved very high accuracy(98%),sensitivity(98%),and specificity(99%).As a result,the fusion process that can help achieve a powerful decision based on different features produced from different filtered images improved the results of the new descriptor of LBP features in terms of accuracy,sensitivity,and specificity.

关键词： Breast cancer ultrasound image local binary pattern feature extraction noise reduction filters fusion

Genotyping of Rotavirus in Neonatal Calves with Acute Gastroenteritis in Iraq

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Advances in Microbiology 2017年第12期7卷 863-870页

作者： Atheer Abdulrazzaq abdulazeez Modher Nagem Abed Department of Microbiology College of Veterinary Medicine University of Baghdad Baghdad Iraq

Globally, Rotavirus is the common major etiologic agents of diarrhea in infant, young children and neonatal calves. It is very important to early diagnose the disease for effective treatment. The objective of this study was to determine the prevalence, molecular characteristics, and the effect of rotavirus strains for severe gastroenteritis in neonatal calves in five Iraqi governorates (Al-Qadissiya, Babel, Kerbala, Missan, Wassit). A total of 125-stool specimens were examined, it have been collected from calves form the period between November 2015 to March 2016. The ages were ranging from 6 to 60 weeks. The specimens were examined using Chromatographic Immunoassay, enzyme-linked immunosorbent assay (ELISA) and Polymerase-chain reaction (PCR). Our results gave us 67 (53.6%) positive by chromatographic immunoassay, 45 (36%) positive by ELISA and 32 (25.6%) positive by PCR. Genotyping were analyzed by multiplex PCR. Genotype combination G1P[8] was (30%) followed by G1P[4] (20%), G3P[4] (20%), G2P[4] (10%), G2P[8] (10%) and G9P[4] (10%). Such information will not only aid in seeking advocacy for introducing rotavirus vaccine in national immunization program in Iraq, but will also help in the evaluation of the efficacy of these vaccines in relation to the rotavirus genotyping circulation.

关键词： Rotavirus Genotyping Calve Diagnosis PCR