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Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

Computer Systems Science & Engineering 2023年第5期45卷 1917-1934页

作者： El-Sayed M.El-kenawy Abdelaziz a.abdelhamid Abdelhameed Ibrahim Seyedali Mirjalili Nima Khodadad Mona A.Al duailij Amel Ali Alhussan Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and *** metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization *** novel optimization methodologies are still *** Al-Biruni earth radius(BER)search optimization algorithm is proposed in this *** proposed algorithm was motivated by the behavior of swarm members in achieving their global *** search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization *** results show that BER can both explore and avoid local *** has also been tested on an engineering design optimization *** results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

关键词： Metaheuristics evolutionary optimization exploration exploitation mutation Al-biruni earth radius

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Advances in Control Technologies for Wastewater Treatment Processes:Status, Challenges, and Perspectives

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 337-363页

作者： abdelhamid Iratni Ni-Bin Chang the Department of Electrical Engineering Faculty of Science and Technology University of Bordj Bou Arreridj IEEE the Civil Environmental and Construction Engineering Department University of Central Florida

This paper presents a thorough review of control technologies that have been applied to wastewater treatment processes in the environmental engineering regime in the past four decades. It aims to provide a comprehensive technological review for both water engineering professionals and control specialists, giving rise to a suite of up-to-date pathways to impact this field in light of the classified technology hubs. The assessment was conducted with respect to linear control, linearizing control,nonlinear control, and artificial intelligence-based control. The application domain of each technology hub was summarized into a set of comparative tables for a holistic assessment. Challenges and perspectives were offered to these field engineers to help orient their future endeavor.

关键词： Control technologies system engineering wastewater treatment

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Meta-heuristics for Feature Selection and Classification in Diagnostic Breast Cancer

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Computers, Materials & Continua 2022年第10期73卷 749-765页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Ali E.Takieldeen Tarek M.Hassan Ehab A.Hegazy Elsayed Abdel Fattah Eid Abdelhameed Ibrahim Abdelaziz a.abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Communications and Computers Engineering Department Faculty of EngineeringDelta University for Science and TechnologyInternational Coastal RoadGamasa CityDakhliyaEgypt Faculty of Applied Health Science Technology Delta University for Science and TechnologyMansoura35712Egypt Faculty of Medicine Head of Internal Medicine DepartmentDelta University for Science and TechnologyMansouraEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

One of the most common kinds of cancer is breast *** early detection of it may help lower its overall rates of *** this paper,we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal *** proposed approach starts with data preprocessing the input images and segmenting the significant regions of *** addition,to properly train the machine learning models,data augmentation is applied to increase the number of segmented regions using various scaling *** the other hand,to extract the relevant features from the breast cancer cases,a set of deep neural networks(VGGNet,ResNet-50,AlexNet,and GoogLeNet)are *** resulting set of features is processed using the binary dipper throated algorithm to select the most effective features that can realize high classification *** selected features are used to train a neural network to finally classify the thermal images of breast *** achieve accurate classification,the parameters of the employed neural network are optimized using the continuous dipper throated optimization *** results show the effectiveness of the proposed approach in classifying the breast cancer cases when compared to other recent approaches in the ***,several experiments were conducted to compare the performance of the proposed approach with the other *** results of these experiments emphasized the superiority of the proposed approach.

关键词： Breast cancer image segmentation dipper throated optimization feature selection meta-heuristics

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Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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Computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz a.abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

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Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

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Computers, Materials & Continua 2022年第11期73卷 4193-4210页

作者： Nagwan Abdel Samee El-Sayed M.El-Kenawy Ghada Atteia Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz a.abdelhamid Noha E.El-Attar Tarek Gaber Adam Slowik Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura 35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityEgypt School of Science Engineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt Koszalin University of Technology Poland Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

As corona virus disease(COVID-19)is still an ongoing global outbreak,countries around the world continue to take precautions and measures to control the spread of the *** of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals,a rapid,reliable,and automatic detection of COVID-19 is in extreme need to curb the number of *** analyzing the COVID-19 chest X-ray images,a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm *** lung region was segmented from the original chest X-ray images and augmented using various transformation ***,the augmented images were fed into the VGG19 deep network for feature *** the other hand,a feature selection method is proposed to select the most significant features that can boost the classification ***,the selected features were input into an optimized neural network for *** neural network is optimized using the proposed hybrid *** experimental results showed that the proposed method achieved 99.88%accuracy,outperforming the existing COVID-19 detection *** addition,a deep statistical analysis is performed to study the performance and stability of the proposed *** results confirm the effectiveness and superiority of the proposed approach.

关键词： Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning

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Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

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Frontiers in Energy 2020年第4期14卷 836-849页

作者： Abdelkarim AMMAR Amor BOUREK abdelhamid BENAKCHA LGEB Laboratory Department of Electrical EngineeringUniversity of BiskraBiskraBP 145Algeria

This paper proposes a design of control and estimation strategy for induction motor based on the variable structure *** describes a coupling of sliding mode direct torque control(DTC)with sliding mode flux and speed *** algorithm uses direct torque control basics and the sliding mode approach.A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC draw・backs and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple *** sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation(SVM)*** second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation,and consequently,increase the reliability of the system and decrease the cost of using *** effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.

关键词： induction motor direct torque control(DTC) space vector modulation(SVM) sliding mode control(SMC) sliding mode observer(SMO) dS1104

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Cauchy-Stieltjes Kernel Families and Free Multiplicative Convolution

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Communications in Mathematics and Statistics 2024年第4期12卷 679-694页

作者： Raouf Fakhfakh abdelhamid Hassairi College of Science and Arts in Gurayat Jouf UniversityGurayatSaudi Arabia Laboratory of Probability and Statistics Sfax UniversitySfaxTunisia

In this paper,we determine the effect of the free multiplicative convolution on the pseudo-variance function of a Cauchy-Stieltjes kernel *** then use the machinery of variance functions to establish some limit theorems related to this type of convolution and involving the free additive convolution and the Boolean additive convolution.

关键词： Variance function Cauchy kernel Free multiplicative convolution S-transform

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Adsorption of dyes onto activated carbon prepared from olive stones

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Journal of Environmental Sciences 2005年第6期17卷 998-1003页

作者： Souad NAJAR-SOUISSI Abdelmottaleb OUEDERNI abdelhamid RATEL Chemical Reactors and Process Control National School of Engineers of Gabes Medenine Street 6029 Tunisia Chemical Reactors and Process Control National School of Engineers of Gabes Medenine Street 6029 Tunisia Chemical Reactors and Process Control National School of Engineers of Gabes Medenine Street 6029 Tunisia

Activated carbon was produced from olive stones（OSAC） by a physical process in two steps. The adsorption character of this activated carbon was tested on three colour dyes molecules in aqueous solution： Methylene blue（MB）, Rhodamine B（RB） and Congo Red（CR）. The adsorption equilibrium was studied through isotherms construction at 30℃, which were well described by Langmuir model. The adsorption capacity on the OSAC was estimated to be 303 mg/g, 217 mg/g and 167 mg/g respectively for MB, RB and CR. This activated carbon has a similar adsorption properties to that of commercial ones and show the same adsorption performances. The adsorption kinetics of the MB molecule in aqueous solution at different initial concentrations by OSAC was also studied. Kinetic experiments were well fitted by a simple intra-particle diffusion model. The measured kinetics constant was influenced by the initial concentration and we found the following correlation： Kid = 1.55 C0^0.51.

关键词： activated carbon olive stones adsorption dyes isotherms kinetic

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A NEW HYBRIDIZED MIXED WEAK GALERKIN METHOD FOR SECOND-ORDER ELLIPTIC PROBLEMS

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Journal of Computational Mathematics 2022年第4期40卷 499-516页

作者： abdelhamid Zaghdani Sayed Sayari Miled EL Hajji University of Tunis Boulevard du 9 avril 1939 TunisDepartment of MathematicsEnsitTaha Hussein AvenueMontfleuryTunisTunisia Northern Border University Faculty of Arts and ScienceRafhaP.O.840Saudi Arabia Carthage University Isteub2 Rue de l’Artisanat Charguia 22035 TunisTunisia Department of Mathematics Faculty of SciencesUniversity of JeddahSaudi Arabia ENIT-LAMSINBP.371002 Tunis-Belv´ed`ereTunis El Manar UniversityTunisia

In this paper,a new hybridized mixed formulation of weak Galerkin method is studied for a second order elliptic *** method is designed by approximate some operators with discontinuous piecewise polynomials in a shape regular finite element *** discrete inequalities are presented on discontinuous spaces and optimal order error estimations are *** numerical results are reported to show super convergence and confirm the theory of the mixed weak Galerkin method.

关键词： Weak Galerkin Weak gradient Hybridized mixed finite element method Second order elliptic problems

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A New Non-centrosymmetric Microporous Fluorinated Iron Phosphate： Structural Elucidation, Spectroscopic Study and Hirshfeld Surface Analysis

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Chemical Research in Chinese Universities 2016年第4期32卷 519-526页

作者： Nabaa BOUZIDIA Besma HAMDI abdelhamid BEN SALAH Laboratory of Materials Science and Environment Faculty of Sciences of Sfax University of Sfax PB 1171 3000 SFAX Tunisia

The crystal structure of a new non-centrosymmetric microporous fluorinated iron phosphate, （H30）2[Fe4（H2O）2F4（PO4）2（HPO4）2]（H2O）, was determined by single crystal X-ray diffraction analysis and the result reveals that it belongs to the orthorhombic system with four molecules in the unit cell（space group P212121）. Thus, the complex was characterized by powder X-ray diffraction, spectroscopic techniques（Fourier transform infrared and Fourier transform Raman） and 19F MAS NMR. The elemental analysis of the sample was also carried out. The chiral inorganic sheets, which stacked along [100] showed the presence of FeF2O4 as well as FeF2O3H2O octahedra, PO4 besides HPO4 tetrahedra, hydronium ions（H3O＋） and isolated water molecules. Hirshfeld surface analysis, especially dnom surface and fingerprint plots, were used for decoding the intermolecular interactions in the crystal network and the contribution of component units for the construction of the 3D architecture. From the Hirshfeld surfaces and 2D fingerprint analysis, it was found that the subtle interactions, such as H...H associating the third intense interaction of all intercontacts, provide extra stabilization in addition to the presence of the strong hydrogen bonds mentioned above.

关键词： Non-centrosymmetric structure Iron fluorinated phosphate Hirshfeld surface analysis

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