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The Relationship between Serum 25-Hydroxyvitamin D and Resistin Levels in Saudi Diabetic Patients

Open Journal of Endocrine and Metabolic Diseases 2016年第2期6卷 102-108页

作者： ahmed El-Tahir Abdulaziz F. AL-Kaabbab muaawia ahmed hamza Abdullah A. Saeed Abdulshakour Abdalla May F. AlMohareb Hana S. Alfaleh Gwiria M. H. Satti Faculty of Medicine King Fahad Medical City Ministry of Health Kingdom of Saudi Arabia Faculty of Medicine Al-Imam Mohammed Ibn Saud Islamic University Kingdom of Saudi Arabia Faculty of Medicine University of Khartoum Sudan

Objectives: The aim of this study was to investigate the relationship between the levels of 25-hydroxyvitamin D and the adipokine resistin in Saudi diabetic patients and those at high risk to develop atherosclerotic cardiovascular diseases. Methodology: One hundred and sixty seven subjects were recruited for the cross-sectional study at King Fahad Medical City, Saudi Arabia. Blood samples were analyzed for biochemical parameters. Serum 25-hydroxyvitamin D and resistin levels were measured for all the participants. Result: Fifty six type-1, 55 type-2 diabetic patients and 56 healthy controls were recruited. Serum 25-hydroxyvitamin D level in the control group was 44.21 ± 41.80 μg/ml compared to 50.67 ± 35.60 μg/ml in the diabetic group (P = 0.427) with no significant different between type-2 diabetes mellitus and type-1 diabetes mellitus (P = 0.628). Resistin level in the control group was 14.00 ± 7.39μg/ml compared to 20.21 ± 16.94 μg/ml in the diabetic group (P ≤ 0.01), no significant difference between type-2 diabetes mellitus and type-1 diabetes mellitus (P = 0.817). Resistin in those taking vitamin D supplementation was 21.34 ± 18.27 μg/ml;and in those not taking vitamin D supplementation, it was 17.4 ± 11.19 μg/ml;(P = 0.237). There was significant negative correlation between 25-hydroxyvitamin D and resistin in type-2 diabetes mellitus (P ≤ 0.043) and no significant correlation was found between vitamin 25 (OH) D and resistin level in type-1 diabetes mellitus (P = 0.538). Blood urea and creatinine showed significant positive correlation with vitamin 25 (OH) D in one hand and resistin level on the other hand. Discussion and Conclusions: Several in vitro and in vivo studies have confirmed that the vitamin 25 (OH) D have numerous important functions in the body. The circulating vitamin 25 (OH) D and resistin levels were associated with general inflammation in renal diseases. This study showed significant negative correlation between resistin level and vitamin 25

关键词： 25-Hydroxyvitamin D Resistin Diabetes Mellitus Kingdom of Saudi Arabia

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Coronavirus Detection Using Two Step-AS Clustering and Ensemble Neural Network Model

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Computers, Materials & Continua 2022年第6期71卷 6307-6331页

作者： ahmed hamza Osman Department of Information System Faculty of Computing and Information Technology King Abdulaziz University RabighSaudi Arabia

This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical *** proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chestX-ray images through Two Step-As clustering algorithm with rich filter families,abstraction and weight-sharing *** contrast to the generally used transformational learning approach,the proposed model was trained before and after *** compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to each new group,with each subject group displayed as a distinct *** retrieved characteristics discriminant cases were used to feed the Multiple Neural Network method,which was then utilised to classify the *** Two Step-AS clustering method has been modified by pre-aggregating the dataset before applying Multiple Neural Network algorithm to detect COVID-19 cases from chest X-ray *** forMultiple Neural Network and Two Step-As clustering algorithms were optimised by utilising Ensemble Bootstrap Aggregating algorithm to reduce the number of hyper parameters they *** testswere carried out using theCOVID-19 public radiology database,and a cross-validationmethod ensured *** proposed classifier with an accuracy of 98.02%percent was found to provide the most efficient outcomes *** result is a lowcost,quick and reliable intelligence tool for detecting COVID-19 infection.

关键词： Two step-AS clustering ensemble learning bootstrap aggregating multiple neural network covid-19 X-ray images

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Hyperparameter Tuned Deep Hybrid Denoising Autoencoder Breast Cancer Classification on Digital Mammograms

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Intelligent Automation & Soft Computing 2023年第6期36卷 2879-2895页

作者： Manar ahmed hamza Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Breast Cancer(BC)is considered the most commonly scrutinized can-cer in women worldwide,affecting one in eight women in a ***-phy screening becomes one such standard method that is helpful in identifying suspicious masses’malignancy of BC at an initial ***,the prior iden-tification of masses in mammograms was still challenging for extremely dense and dense breast categories and needs an effective and automatic mechanisms for helping radiotherapists in *** learning(DL)techniques were broadly utilized for medical imaging applications,particularly breast mass *** advancements in the DL field paved the way for highly intellectual and self-reliant computer-aided diagnosis(CAD)systems since the learning cap-ability of Machine Learning(ML)techniques was constantly *** paper presents a new Hyperparameter Tuned Deep Hybrid Denoising Autoenco-der Breast Cancer Classification(HTDHDAE-BCC)on Digital *** presented HTDHDAE-BCC model examines the mammogram images for the identification of *** the HTDHDAE-BCC model,the initial stage of image preprocessing is carried out using an average median *** addition,the deep convolutional neural network-based Inception v4 model is employed to generate feature *** parameter tuning process uses the binary spider monkey opti-mization(BSMO)*** HTDHDAE-BCC model exploits chameleon swarm optimization(CSO)with the DHDAE model for BC *** experimental analysis of the HTDHDAE-BCC model is performed using the MIAS *** experimental outcomes demonstrate the betterments of the HTDHDAE-BCC model over other recent approaches.

关键词： Digital mammograms breast cancer classification computer-aided diagnosis deep learning metaheuristics

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Reforming of Methane by CO2 over Bimetallic Ni-Mn/γ-Al2O3 Catalyst

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Chinese Journal of Chemical Physics 2014年第2期27卷 214-220,I0004页

作者： Anis hamza Fakeeha Muhammad Awais Naeem Wasim Ullah Khan ahmed Elhag Abasaeed ahmed Sadeq Al-Fatesh 沙特国王大学工程学院化学工程系利雅得11421

γ-Al2O3 supported Ni-Mn bimetallic catalysts for CO2 reforming of methane were prepared by impregnation method. The reforming reactions were conducted at 500-700℃ and atmospheric pressure using CO2/CH4/N2 with feed ratio of 17/17/2, at total flow rate of 36 mL/min. The catalytic performance was assessed through CH4 and CO2 conversions, synthesis gas ratio （H2/CO） and long term stability. Catalytic activity and stability tests revealed that addition of Mn improved catalytic performance and led to higher stability of bimetallic catalysts which presented better coke suppression than monometallic catalyst. In this work, the optimum loading of Mn which exhibited the most stable performance and least coke deposition was 0.5wt%. The fresh and spent catalysts were characterized by various techniques such as Brunauer-Emmett-Teller, the temperature programmed desorption CO2- TPD, thermogravimetric analysis, X-ray diffraction, scanning electron microscope, EDX, and infrared spectroscopy.

关键词： CH4 CO2 Bimetallic Dry reforming Ni/γ-Al2O3 Mn and H2/CO

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DFT Investigation of Structural,Electronic,Elastic and Optical Properties of SrMO_4(M=Mo and W)

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Communications in Theoretical Physics 2017年第10期67卷 536-544页

作者： hamza Gueffaf Brahim Lagoun Abdelnasser Guibadj Said Maabed ahmed Gueddouh Laboratoire de Physico-chimie des Matériaux Université Amar Telidji de Laghouat Department of Material Sciences Université Amar Telidji Laghouat Laboratoire de Physique des Matériaux Université Amar Telidji de Laghouat

A planes waves pseudo-potential calculations are performed for the SrMO4 （M=Mo and W） compound in order to investigate the structural, electronic, elastic and optical properties. The calculated lattice constants are in good agreement with experiment ones. The electronic structures show that SrMO4 has a direct band gap situated at F point. The calculated elastic constants indicate that both structures are mechanically stable. The bulk modulus, shear modulus, Young＇s modulus and Poisson ratio are investigated from the elastic constants, in the same time the anisotropy of the elastic properties is discussed. The imaginary part of the dielectric functions is calculated and the contributions of various transitions peaks are analyzed. Furthermore, the other optical properties such as absorption coefficient I（w）, optical reflectivity R（w）, energy-loss spectrum L（w）, and the refractive index n（w） have been investigated.

关键词： SrMoO4 SrWO4 DFT electronic structure elastic properties opticai properties

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Automated Video-Based Face Detection Using Harris Hawks Optimization with Deep Learning

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Computers, Materials & Continua 2023年第6期75卷 4917-4933页

作者： Latifah Almuqren Manar ahmed hamza Abdullah Mohamed Amgad Atta Abdelmageed Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Face recognition technology automatically identifies an individual from image or video *** detection process can be done by attaining facial characteristics from the image of a subject *** developments in deep learning(DL)and computer vision(CV)techniques enable the design of automated face recognition and tracking *** study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking(HHODL-AFDT)*** proposed HHODL-AFDT model involves a Faster region based convolution neural network(RCNN)-based face detection model and HHO-based hyperparameter opti-mization *** presented optimal Faster RCNN model precisely rec-ognizes the face and is passed into the face-tracking model using a regression network(REGN).The face tracking using the REGN model uses the fea-tures from neighboring frames and foresees the location of the target face in succeeding *** application of the HHO algorithm for optimal hyperparameter selection shows the novelty of the *** experimental validation of the presented HHODL-AFDT algorithm is conducted using two datasets and the experiment outcomes highlighted the superior performance of the HHODL-AFDT model over current methodologies with maximum accuracy of 90.60%and 88.08%under PICS and VTB datasets,respectively.

关键词： Face detection face tracking deep learning computer vision video surveillance parameter tuning

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Response of basement wall in tall buildings foundation under lateral loading

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Frontiers of Structural and Civil Engineering 2022年第11期16卷 1415-1423页

作者： Irfan JAMIL Irshad AHMAD Aqeel Ur REHMAN Aqib ahmed Ameer hamza Wali ULLAH Department of Civil Engineering University of Engineering and TechnologyPeshawar 25000Pakistan

With increasing population and limitation of availability of land,tall buildings supported on piled raft foundations are increasingly used in the modern *** increase the ratio of floor area to height,and to fulfill storage and parking facilities requirements,these tall buildings usually have more than one basement ***,during the foundation design,engineers have not considered the basement wall contribution to resisting lateral load induced by earthquake or wind and this can result in an uneconomical construction of *** this research work,an experimental study was performed on small-scale models,in order to study basement wall contribution,and the raft contribution including for piled raft foundations,to resisting lateral *** configurations of piles in 2×2,2×3,and 3×3 patterns were tested as a pile group,piled raft and piled raft with a basement *** show that when a basement wall is present,the lateral displacement decreases and the demand on each pile *** piled raft design can become more economical for tall buildings if the basement’s walls are taken into account.

关键词： basement wall lateral load displacement piled raft

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Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification

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Computers, Materials & Continua 2022年第8期72卷 2859-2875页

作者： Areej A.Malibari Siwar Ben Haj Hassine Abdelwahed Motwakel Manar ahmed hamza Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayilAsirSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Atherosclerosis diagnosis is an inarticulate and complicated cognitive *** on medical diagnosis necessitate maximum accuracy and performance to make optimal clinical *** the medical diagnostic outcomes need to be prompt and accurate,the recently developed artificial intelligence(AI)and deep learning(DL)models have received considerable attention among research *** study develops a novel Metaheuristics with Deep Learning Empowered Biomedical Atherosclerosis Disease Diagnosis and Classification(MDL-BADDC)*** proposed MDL-BADDC technique encompasses several stages of operations such as pre-processing,feature selection,classification,and parameter ***,the proposed MDL-BADDC technique designs a novel Quasi-Oppositional Barnacles Mating Optimizer(QOBMO)based feature selection ***,the deep stacked autoencoder(DSAE)based classification model is designed for the detection and classification of atherosclerosis ***,the krill herd algorithm(KHA)based parameter tuning technique is applied to properly adjust the parameter *** order to showcase the enhanced classification performance of the MDL-BADDC technique,a wide range of simulations take place on three benchmarks biomedical *** comparative result analysis reported the better performance of the MDL-BADDC technique over the compared methods.

关键词： Atherosclerosis disease biomedical data data classification machine learning disease diagnosis deep learning

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Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

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Computers, Materials & Continua 2022年第7期72卷 1951-1965页

作者： Manar ahmed hamza Abdelzahir Abdelmaboud Souad Larabi-Marie-Sainte Haya Mesfer Alshahrani Mesfer Al Duhayyim hamza Awad Ibrahim Mohammed Rizwanullah Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information Systems College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityP.O.Box No.66833Rafha StreetRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia College of Computer at Al-Gunfudah Umm Al-Qura UniversityAl-Gunfudah24382Saudi Arabia

Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the ***,the quality of test cases has a considerable influence on fault revealing capability of software testing *** Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution *** ismainly intended to design a collection of test cases that can accomplish early optimization using preferred *** studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software *** this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software *** aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution *** addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO *** order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several *** experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

关键词： Software testing harris hawks optimization test case prioritization apfd execution time metaheuristics

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Deep Consensus Network for Recycling Waste Detection in Smart Cities

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Computers, Materials & Continua 2023年第5期75卷 4191-4205页

作者： Manar ahmed hamza Hanan Abdullah Mengash Noha Negm Radwa Marzouk Abdelwahed Motwakel Abu Sarwar Zamani Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz University16278AlKharjSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia

Recently,urbanization becomes a major concern for developing as well as developed *** to the increased urbanization,one of the important challenging issues in smart cities is waste ***,automated waste detection and classification model becomes necessary for the smart city and to accomplish better recyclable waste *** recycling of waste offers the chance of reducing the quantity of waste disposed to the land fill by minimizing the requirement of collecting raw *** study develops a novel Deep Consensus Network with Whale Optimization Algorithm for Recycling Waste Object Detection(DCNWORWOD)in Smart *** goal of the DCNWO-RWOD technique intends to properly identify and classify the objects into recyclable and non-recyclable *** proposed DCNWO-RWOD technique involves the design of deep consensus network(DCN)to detect waste objects in the input *** improving the overall object detection performance of the DCN model,the whale optimization algorithm(WOA)is ***,Na飗e Bayes(NB)classifier is used for the classification of detected waste objects into recyclable and non-recyclable *** performance validation of theDCNWO-RWOD technique takes place using the open access *** extensive comparative study reported the enhanced performance of the DCNWO-RWOD technique interms of several measures.

关键词： Smart city waste management object detection recycling deep consensus network

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