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Impact of partial slip condition on mixed convection of nanofluid within lid-driven wavy cavity and solid inner body

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Propulsion and Power Research 2022年第4期11卷 544-564页

作者： ammar I.Alsabery Mohammad H.Yazdi Ali S.Abosinnee Ishak Hashim Evgeny Solomin Refrigeration&Air-conditioning Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajafIraq New Materials Technology and Processing Research Center Department of Mechanical EngineeringNeyshabur BranchIslamic Azad UniversityNeyshaburIran Altoosi University College NajafIraq Department of Mathematical Sciences Faculty of Science&TechnologyUniversiti Kebangsaan Malaysia43600Bangi SelangorMalaysia Department of Electric Power Generation Stations Network and Supply SystemsInstitute of Engineering and TechnologySouth Ural State University76Lenin AvenueChelyabinsk454080Russian Federation

In thermofluid systems,the lid-driven square chamber plays an imperative role in analyzing thermodynamics’first and second laws in limited volume cases executed by sheer effects with a prominent role in many industrial applications including electronic cooling,heat exchangers,microfluidic components,solar collectors,and renewable ***,nanofluids as working fluids have demonstrated potential for heat transfer enhancement systems,however there are some concerns about irreversibility problems in the *** to this problem and in line with the applications of partial slip on fluid flow modification and irreversibilities,the present study considers laminar mixed convection and entropy generation analysis of aluminum oxide nanofluid inside a lid-driven wavy cavity having an internal conductive solid body in the presence of a partial slip on the upper surface,which to the best of our knowledge,has not been investigated so *** fundamental equations of the current work with the appropriate boundary conditions are first made dimensionless and then solved numerically using the Galerkin weighted residual *** main parameters of the flow and heat transfer,entropy generation,and Bejan number are presented and explained in *** outcomes indicate that the partial slip is more effective when friction irreversibilities govern the *** the presence of slip condition,the flow circulation changes the trend in the middle of the cavity around the solid block leading to a decrease in the isentropic lines at the dense sections with almost 30%less than the case of no-slip *** is concluded that partial slip shows different trends on the local Nusselt number interface along the wavy wall improving the average Nusselt number where high friction irreversibilities dominate.

关键词： Entropy generation Mixed convection Lid-driven wavy cavity Nanofluid Inner cylinder Partial slip

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Fast Intra Mode Selection in HEVC Using Statistical Model

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Computers, Materials & Continua 2022年第2期70卷 3903-3918页

作者： Junaid Tariq Ayman Alfalou Amir Ijaz Hashim Ali Imran Ashraf Hameedur Rahman ammar Armghan Inzamam Mashood Saad Rehman Department of Computer Science&Engineering HITEC UniversityTaxilaPakistan L@BISEN Equipe LSLYncrea Oust20 rue Cuirasse BretagneBrest29200France Department of IT and CS Pak-Austria FachhochschuleHaripurPakistan Department of Electrical Engineering Jouf UniversitySakakaKSA

Comprehension algorithms like High Efficiency Video Coding(HEVC)facilitates fast and efficient handling of multimedia *** algorithms involve various computation modules that help to reduce the size of content but preserve the same subjective viewing ***,the brute-force behavior of HEVC is the biggest hurdle in the communication of multimedia ***,a novel method will be presented here to accelerate the encoding process of HEVC by making early intra mode decisions for the ***,the HEVC applies 35 intra modes to every block of the frame and selects the best among them based on the RD-cost(rate-distortion).Firstly,the proposed work utilizes neighboring blocks to extract available information for the current *** this information is converted to the probability that tells which intra mode might be best in the current *** proposed model has a strong foundation as it is based on the probability rule-2 which says that the sum of probabilities of all outcomes should be ***,it is also based on optimal stopping theory(OST).Therefore,the proposed model performs better than many existing OST and classical *** proposed algorithms expedited the encoding process by 30.22%of the HEVC with 1.35%Bjontegaard Delta Bit Rate(BD-BR).

关键词： Statistical HEVC angular mode reduce time

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A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification

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Computer Systems Science & Engineering 2022年第1期40卷 223-235页

作者： Adi Alhudhaif ammar Saeed Talha Imran Muhammad Kamran Ahmed S.Alghamdi Ahmed O.Aseeri Shtwai Alsubai Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Cantt47010Pakistan University of Jeddah College of Computer Science and Engineering Department of CybersecurityJeddah21959Saudi Arabia

Image classification is a core field in the research area of image proces-sing and computer vision in which vehicle classification is a critical *** purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security,traffic analysis,and self-driving and autonomous *** recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional,and handcrafted means of solving image analysis *** this paper,a combina-tion of pre-trained CNN GoogleNet and a nature-inspired problem optimization scheme,particle swarm optimization(PSO),was employed for autonomous vehi-cle *** model was trained on a vehicle image dataset obtained from Kaggle that has been suitably *** trained model was classified using several classifiers;however,the Cubic SVM(CSVM)classifier was found to out-perform the others in both time consumption and accuracy(94.8%).The results obtained from empirical evaluations and statistical tests reveal that the model itself has shown to outperform the other related models not only in terms of accu-racy(94.8%)but also in terms of training time(82.7 s)and speed prediction(380 obs/sec).

关键词： Vehicle classification intelligent transport system deep learning constrained machine learning particle swarm optimization CNN GoogleNet

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Global research production pertaining to gastrointestinal involvement in COVID-19:A bibliometric and visualised study

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World Journal of Gastrointestinal Surgery 2022年第5期14卷 494-505页

作者： Sa'ed H Zyoud Samah W Al-Jabi Moyad Jamal Shahwan ammar Abdulrahman Jairoun Department of Clinical and Community Pharmacy College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Poison Control and Drug Information Center College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Clinical Research Centre An-Najah National University HospitalNablus 44839Palestine Department of Clinical Sciences College of Pharmacy and Health SciencesAjman UniversityAjman 346United Arab Emirates Centre of Medical and Bio-allied Health Sciences Research Ajman UniversityAjman 346United Arab Emirates Department of Health and Safety Dubai MunicipalityDubai 67United Arab Emirates

BACKGROUND Coronavirus disease 2019(COVID-19)is a global pandemic that can cause diarrhoea,nausea/vomiting,and abdominal pain,among other gastrointestinal(GI)*** To perform a bibliometric analysis of the global research production pertaining to GI involvement in *** The Scopus database was used to search the global literature on GI involvement in COVID-19 during 2020.A bibliometric review of these publications was also performed using *** Scopus had published 95615 documents on COVID-19 in all areas of research at the time of data *** total,1267 publications on the topic of GI and COVID-19 were *** articles(n=606;47.83%),letters(293;23.13%),and reviews(186;14.68%)were the most popular types of *** most productive countries and institutions in this field were the United States and Huazhong University of Science and *** most cited paper was Xiao et al,which was published in Gastroenterology as a brief communication,with 798 *** paper provides evidence for GI infection of COVID-19 and its possible faecal–oral transmission *** the term cluster analysis,there were two frontiers in this field:GI manifestations among COVID-19 patients and the implications of COVID-19 for the *** GI manifestations among COVID-19 patients and implications of COVID-19 for gastroenterologists were of interest,especially in the early stages of the pandemic.

关键词： COVID-19 Gastrointestinal Symptoms Bibliometric Scopus

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Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

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Computer Systems Science & Engineering 2023年第5期45卷 1775-1787页

作者： Abdelhamied A.Ateya Amel Ali Alhussan Hanaa A.Abdallah Mona A.Al duailij Abdukodir Khakimov ammar Muthanna Department of Electronics and Communications Engineering Zagazig UniversityZagazigSharqia44519Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Applied Probability and Informatics Peoples’Friendship University of Russia(RUDN University)Moscow117198Russia Center for Telecommunication Research School of Postgraduate Studies&ResearchSri Lanka Technological CampusPadukka10500Sri Lanka

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability,availability,and ultra-low *** requirements of such networks are the main challenges that can be handled using a range of recent technologies,including multi-access edge computing(MEC),artificial intelligence(AI),millimeterwave communications(mmWave),and software-defined *** aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service(QoS).This article considers developing a complex MEC structure for fifth and sixth-generation(5G/6G)cellular ***,we propose a seamless migration technique for complex edge computing *** developed migration scheme enables services to adapt to the required load on the radio *** proposed algorithm is analyzed for various use cases,and a test bench has been developed to emulate the operator’s *** obtained results are introduced and discussed.

关键词： 5G 6G mobile edge computing migration offloading quality of service

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Classification of Nonlinear Confusion Component Using Hybrid Multi-Criteria Decision Making

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Intelligent Automation & Soft Computing 2023年第5期36卷 1451-1463页

作者： Nabilah Abughazalah Iqra Ishaque Majid Khan ammar S.Alanazi Iqtadar Hussain Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Applied Mathematics and Statistics Institute of Space TechnologyIslamabadPakistan Department of Mathematics King Abdulaziz UniversityFaculty of ScienceJeddahSaudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar Statistical Consulting Unit College of Arts and ScienceQatar UniversityDohaQatar

In today’s digital world,the most inevitable challenge is the protection of digital *** to the weak conﬁdentiality preserving techniques,the existing world is facing several digital information *** make our digital data indecipherable to the unauthorized person,a technique forﬁnding a crypto-graphically strong Substitution box(S-box)have *** S-box with sound cryptographic assets such as nonlinearity(NL),strict avalanche criterion(SAC),bit independence criteria(BIC),bit independence criteria of nonlinearity(BIC-NL),Bit independence criteria of Strict avalanche criteria(BIC-SAC),and Input/output XOR is considered as the robust *** Decision-Making Trial and Evaluation Laboratory(DEMATEL)approach of multi-criteria decision making(MCDM)is proposed forﬁnding the interrelation among cryptographic properties.A combination of two MCDM methods namely Entropy and multi-objective optimization based on ratio analysis(MOORA)is applied for the best S-box selection.A robust substitution box is selected for secure communications in cryptography by using the combination of DEMETAL selection criteria,entro-py weight assigning,and MOORA ranking *** combination of these three methods provides a fast selection procedure for the secure confusion *** offered selection method can also be utilized for the choice of the best cryptosystem with highly secure properties and resistive against all possible linear and differential attacks in the cryptanalysis.

关键词： DEMATEL MCDM MOORA nonlinearity S-box

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BLOWING UP AND MULTIPLICITY OF SOLUTIONS FOR A FOURTH-ORDER EQUATION WITH CRITICAL NONLINEARITY

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Acta Mathematica Scientia 2015年第6期35卷 1511-1546页

作者： Siwar ammar Mokhles HAMMAMI Department of mathematics University of Monastir Department of mathematics Faculty of Sciences of sfax University of Sfax

In this paper, we consider the following nonlinear elliptic problem ： △2u =｜u｜n-4^-u＋u｜u｜q-1u,in Ω,△u=u=0 on ЭΩ,where Ω is a bounded and smooth domain in R^n,n∈{5,6,7},u is a parameter and q∈]4/（n-4）,（12-n）/（n-4）].We study the solutions which concentrate around two points of Ω. We prove that the concentration speeOs are the same order and the distances of the concentration points from each other and from the boundary are bounded. For Ω=（Ωa）a a smooth ringshaped open set, we establish the existence of positive solutions which concentrate at two points of Ω. Finally, we show that for u〉0, large enough, the problem has at least many positive solutions as the Ljusternik-Schnirelman category of Ω.

关键词： fourth order elliptic equations critical Sobolev exponent blow up solution

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GaitDONet: Gait Recognition Using Deep Features Optimization and Neural Network

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Computers, Materials & Continua 2023年第6期75卷 5087-5103页

作者： Muhammad Attique Khan Awais Khan Majed Alhaisoni Abdullah Alqahtani ammar Armghan Sara A.Althubiti Fayadh Alenezi Senghour Mey Yunyoung Nam Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka 72388Saudi Arabia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of ICT Convergence Soonchunhyang UniversityKorea

Human gait recognition(HGR)is the process of identifying a sub-ject(human)based on their walking *** subject is a unique walking pattern and cannot be simulated by other ***,gait recognition is not easy and makes the system difficult if any object is carried by a subject,such as a bag or *** article proposes an automated architecture based on deep features optimization for *** our knowledge,it is the first architecture in which features are fused using multiset canonical correlation analysis(MCCA).In the proposed method,original video frames are processed for all 11 selected angles of the CASIA B dataset and utilized to train two fine-tuned deep learning models such as Squeezenet and *** transfer learning was used to train both fine-tuned models on selected angles,yielding two new targeted models that were later used for feature *** are extracted from the deep layer of both fine-tuned models and fused into one vector using *** improved manta ray foraging optimization algorithm is also proposed to select the best features from the fused feature matrix and classified using a narrow neural network *** experimental process was conducted on all 11 angles of the large multi-view gait dataset(CASIA B)dataset and obtained improved accuracy than the state-of-the-art ***,a detailed confidence interval based analysis also shows the effectiveness of the proposed architecture for HGR.

关键词： Human gait recognition biometric deep learning features fusion optimization neural network

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Age and Gender Classification Using Backpropagation and Bagging Algorithms

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Computers, Materials & Continua 2023年第2期74卷 3045-3062页

作者： ammar Almomani Mohammed Alweshah Waleed Alomoush Mohammad Alauthman Aseel Jabai Anwar Abbass Ghufran Hamad Meral Abdalla Brij B.Gupta Research and Innovation Department Skyline University CollegeP.O.Box 1797SharjahUAE IT-department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan Prince Abdullah Ben Ghazi Faculty of Information and Communication Technology Al-Balqa Applied UniversityAl-SaltJordan School of Information Technology Skyline University CollegeSharjah P.O.Box 1797United Arab Emirates Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Department of Computer Science and Information Engineering Asia UniversityTaizhongTaiwan Department of Computer Science King Abdulaziz UniversityJeddahSaudi Arabia

Voice classification is important in creating more intelligent systems that help with student exams,identifying criminals,and security *** main aim of the research is to develop a system able to predicate and classify gender,age,and ***,a newsystem calledClassifyingVoice Gender,Age,and Accent(CVGAA)is *** and bagging algorithms are designed to improve voice recognition systems that incorporate sensory voice features such as rhythm-based features used to train the device to distinguish between the two gender *** has high precision compared to other algorithms used in this problem,as the adaptive backpropagation algorithm had an accuracy of 98%and the Bagging algorithm had an accuracy of 98.10%in the gender identification *** has the best accuracy among all algorithms,with 55.39%accuracy in the voice common dataset and age classification and accent accuracy in a speech accent of 78.94%.

关键词： Classify voice gender accent age bagging algorithms back propagation algorithms AI classifiers

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EXISTENCE OF POSITIVE SOLUTIONS FOR A CLASS OF PARABOLIC EQUATIONS WITH NATURAL GROWTH TERMS AND L^1 DATA

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Acta Mathematica Scientia 2014年第4期34卷 1127-1144页

作者： Kaouther ammar Hicham REDWANE Department of Mathematics Faculty of sciencesTaibah UniversityP.O. Box 344 Al MadinahSaudi Arabia Facult'e des Sciences Juridiques Economiques et SocialesUniversit'e Hassan 1B.P. 784SettatMorocco

We study a class of nonlinear parabolic equations of the type：δb（u）/δt-div（a（x,t,u）△u）＋y（u）｜△u｜^2=f,where the right hand side belongs to L^1（Q）, b is a strictly increasing C^1-function and -div（a（x, t, u）△u） is a Leray-Lions operator. The function g is just assumed to be continuous on R and to satisfy a sign condition. Without any additional growth assumption on u, we prove the existence of a renormalized solution.

关键词： renormalized solutions natural growth terms L^1 data

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