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Forecasting Energy Consumption Using a Novel Hybrid Dipper Throated Optimization and Stochastic Fractal Search Algorithm

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Intelligent Automation & Soft Computing 2023年第8期37卷 2117-2132页

作者： Doaa Sami Khafaga el-Sayed m.el-kenawy Amel Ali Alhussan marwa m.Eid Department of Computer Sciences 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 TechnologyMansouraEgypt

The accurate prediction of energy consumption has effective role in decision making and risk management for individuals and ***,the accurate prediction can be realized using the recent advances in machine learning and predictive *** research proposes a novel approach for energy consumption forecasting based on a new optimization algorithm and a new forecasting model consisting of a set of long short-term memory(LSTm)*** proposed optimization algorithm is used to optimize the parameters of the LSTm-based model to boost its forecasting *** optimization algorithm is based on the recently emerged dipper-throated optimization(DTO)and stochastic fractal search(SFS)algo-rithm and is referred to as dynamic *** prove the effectiveness and superiority of the proposed approach,five standard benchmark algorithms,namely,stochastic fractal search(SFS),dipper throated optimization(DTO),whale optimization algorithm(WOA),particle swarm optimization(PSO),and grey wolf optimization(GWO),are used to optimize the parameters of the LSTm-based model,and the results are compared with that of the proposed *** results show that the proposed DDTOSFS+LSTm can accurately forecast the energy consumption with root mean square error RmSE of 0.00013,which is the best among the recorded results of the other *** addition,statistical experiments are conducted to prove the statistical difference of the proposed *** results of these tests confirmed the expected outcomes.

关键词： Stochastic fractal search dipper throated optimization energy consumption long short-term memory prediction models

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Childhood glaucoma profile in Dakahelia, Egypt: a retrospective study

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International Journal of Ophthalmology(English edition) 2018年第4期11卷 674-680页

作者： Tharwat H.mokbel Eman m.el Hefney Sherein m.Hagras Ahmed A.ALNagdy Amani E.Badawi manal A.Kasem Shereen m.el Shaer mansoura Ophthalmic Center Faculty of Medicine Mansoura University Community and Public Health Department Faculty of Medicine Mansoura University

AIm： To analyze childhood glaucoma regarding its demographics, presentations, different causes and surgical modalities used among patients in Dakahelia and to apply the Childhood Glaucoma Research Network（CGRN） classification retrospectively to evaluate its ***： A retrospective study in which the medical files of all glaucoma patients 〈16 years old presented to mansoura Ophthalmic Center, mansoura University from 2014 to 2017, were retrieved and analyzed. Collected data included： age, gender, laterality, visual acuity（VA）, refraction, intraocular pressure（IOP）, corneal diameter, cup-disc ratio, types and number of surgeries and antiglaucomatous drugs（AGD） at the first and last visit. Prevalence of different subtypes was calculated and means of clinical features were ***： A total of 305 eyes of 207 patients were included classified into 6 groups： primary congenital glaucoma（PCG）, juvenile open angle glaucoma（JOAG）, glaucoma associated with systemic disease, glaucoma associated with ocular anomalies, acquired glaucoma and glaucoma following cataract surgery. PCG was the predominant type（55.1%） followed by acquired glaucoma（29.5%）. males represented 63.8% of the whole studied patients. Glaucoma associated with ocular anomaly group showed the youngest age at diagnosis（21.9±30.0 mo）. The shortest corneal diameter was recorded in post cataract group（10.4±0.5 mm）. Highest cup-disc ratio was found in the PCG group（P〈0.0005）. Glaucoma associated with systemic disease presented with the highest baseline IOP（34.5±5.0 mm Hg）. All the cases with PCG were treated surgically with 21.8% required more than one surgery. The majority of the patients（74.2%） in the acquired group were treated medically. Combined trabeculotomy-trabeculectomy was the most frequent operation done, accounting for 34.5% of all primary surgeries. Ahmed valve implantation comprised 87% of the secondary surgeries. Acquired glaucoma group had the highest percent of eyes with good fin

关键词： childhood glaucoma classification Egypt epidemiology

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Analysis of strong refractive effect within 11Li projectile structure

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Chinese Physics C 2021年第2期45卷 414-425页

作者： Kassem O.Behairy m.el-Azab Farid Awad A.Ibraheem Ola Ramadan m.Anwar Physics Department Aswan UniversityAswan 81528Egypt Physics Department Assiut UniversityAssiut 71516Egypt Physics Department King Khalid UniversityAbhaSaudi Arabia Physics Department Al-Azhar UniversityAssiut 71524Egypt

In the context of the double folding optical model,the strong refractive effect for elastic scattering of 11Li+12C and 11Li+28Si systems at incident energies of 29,50,and 60 meV/n is *** folded potentials are generated based on a variety of nucleon-nucleon interactions with the suggested density distributions for the halo structure of 11Li *** rearrangement term(RT)of the extended realistic density dependent CDm3Y6 effective interaction is *** imaginary potential was taken in the traditional standard Woods-Saxon *** results for the calculated potentials are obtained,with a slight effect of the RT in CDm3Y6 *** reproduction with a normalization factor close to one for the observed angular distributions of the elastic scattering differential cross section has been achieved using the derived *** obtained reaction cross-section is studied as a guide by extrapolating our calculations and previous results.

关键词： optical model elastic and inelastic scattering halo nuclei folding model refraction effect

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Detection Collision Flows in SDN Based 5G Using machine Learning Algorithms

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Computers, materials & Continua 2023年第1期74卷 1413-1435页

作者： Aqsa Aqdus Rashid Amin Sadia Ramzan Sultan S.Alshamrani Abdullah Alshehri el-Sayed m.el-kenawy Department of Computer Science University of Engineering and Technology Taxila47050Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology Al Baha UniversityAl BahaSaudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt

The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of *** traffic control and data forwarding functions are decoupled in software-defined networking(SDN)and allow the network to be *** switch in SDN keeps track of forwarding information in a flow *** SDN switches must search the flow table for the flow rules that match the packets to handle the incoming *** to the obvious vast quantity of data in data centres,the capacity of the flow table restricts the data plane’s forwarding ***,the SDN must handle traffic from across the whole *** flow table depends on Ternary Content Addressable memorable memory(TCAm)for storing and a quick search of regulations;it is restricted in capacity owing to its elevated cost and energy *** the flow table is abused and overflowing,the usual regulations cannot be executed *** this case,we consider lowrate flow table overflowing that causes collision flow rules to be installed and consumes excessive existing flow table capacity by delivering packets that don’t fit the flow table at a low *** study introduces machine learning techniques for detecting and categorizing low-rate collision flows table in SDN,using Feed ForwardNeuralNetwork(FFNN),K-means,and Decision Tree(DT).We generate two network topologies,Fat Tree and Simple Tree Topologies,with the mininet simulator and coupled to the OpenDayLight(ODL)*** efficiency and efficacy of the suggested algorithms are assessed using several assessment indicators such as success rate query,propagation delay,overall dropped packets,energy consumption,bandwidth usage,latency rate,and *** findings showed that the suggested technique to tackle the flow table congestion problem minimizes the number of flows while retaining the statistical consistency of the 5G *** putting the proposed flow method

关键词： 5G networks software-defined networking(SDN) OpenFlow load balancing machine learning(mL) feed forward neural network(FFNN) k-means and decision tree(DT)

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Optimized Ensemble Algorithm for Predicting metamaterial Antenna Parameters

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Computers, materials & Continua 2022年第6期71卷 4989-5003页

作者： el-Sayed m.el-kenawy Abdelhameed Ibrahim Seyedali mirjalili Yu-Dong Zhang Shaima elnazer Rokaia m.Zaki Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt 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 School of Computing and mathematical Sciences University of LeicesterLeicesterLE17RHUK Nile Higher Institute for Engineering and Technology MansouraEgypt Computer and Information Technology College Taif UniversityTaifSaudi Arabia Higher Institute of Engineering and Technology Kafrelsheikh Department of electrical Engineering Shoubra Faculty of EngineeringBenha UniversityEgypt

metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve *** antennas can overcome the bandwidth constraint associated with tiny *** learning is receiving a lot of interest in optimizing solutions in a variety of *** learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today’s *** accuracy of the forecast is mostly determined by the model *** purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the metamaterial *** Vector machines(SVm),Random Forest,K-Neighbors Regressor,and Decision Tree Regressor were utilized as the basic *** Adaptive Dynamic Polar Rose Guided Whale Optimization method,named AD-PRS-Guided WOA,was used to pick the optimal features from the *** suggested model is compared to models based on five variables and to the average ensemble *** findings indicate that the presented model using Random Forest results in a Root mean Squared Error(RmSE)of(0.0102)for bandwidth and RmSE of(0.0891)for *** is superior to other models and can accurately predict antenna bandwidth and gain.

关键词： metamaterial antenna machine learning ensemble model feature selection guided whale optimization support vector machines

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Dynamics of Super Quantum Correlations and Quantum Correlations for a System of Three Qubits

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Communications in Theoretical Physics 2016年第4期65卷 447-452页

作者： F.Siyouri m.el Baz S.Rfifi Y.Hassouni Laboratoire de Physique Theorique Departement de Physique Faculte des sciences Universite Mohammed V - AgdalAv. Ibn Battouta B.P. 1014 Agdal Rabat Morocco

The dynamics of quantum discord for two qubits independently interacting with dephasing reservoirs have been studied *** authors [***.A 88(2013) 034304] found that for some Bell-diagonal states(BDS)which interact with their environments the calculation of quantum discord could experience a sudden transition in its dynamics,this phenomenon is known as the sudden *** in the present paper,we analyze the dynamics of normal quantum discord and super quantum discord for tripartite Bell-diagonal states independently interacting with dephasing ***,we find that basis change does not necessary mean sudden change of quantum correlations.

关键词： super quantum discord normal quantum discord Bell-diagonal states measurement strength

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An Optimized Ensemble model for Prediction the Bandwidth of metamaterial Antenna

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Computers, materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed Ibrahim Hattan F.Abutarboush Ali Wagdy mohamed mohamad Fouad el-Sayed m.el-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(mL)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the metamaterial *** base models are used namely:multilayer Perceptron(mLP)and Support Vector machines(SVm).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

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Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in metamaterial Antenna

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Computers, materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga el-Sayed m.el-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences 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 General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi 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

metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),multi-Layer Perceptron(mLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： metamaterial antenna dipper throated optimization feature selection parameters prediction

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Dipper Throated Optimization for Detecting Black-Hole Attacks inmANETs

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Computers, materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel el-Sayed m.el-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim mostafa Abotaleb Doaa Sami Khafaga 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 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 Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(mANET)continues to be in demand for additional debate and *** more mANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,mANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost mANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-mLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Synthesis of newly cationic surfactant based on dimethylaminopropyl amine and their silver nanoparticles:Characterization;surface activity and biological activity

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Chinese Chemical Letters 2017年第2期28卷 264-273页

作者： Samy m.Shaban Ismail Aiad mohamed m.el-Sukkary E.A.Soliman moshira Y.el-Awady Petrochemical Department Egyptian Petroleum Research Institute Faculty of Science Ain Shams University

The chemical structure of newly synthesized cationic surfactants based on Schiff base was confirmed using Fourier transform infrared spectroscopy,proton nuclear magnetic resonance spectroscopy,and mass *** synthesized surfactants were used in the synthesis of silver nanoparticles by a simple one-step *** silver nanoparticle（AgNPs） formation was confirmed using transmission electron microscopy（TEm）,electron diffraction（SAED）,dynamic light scattering（DLS）,and energy dispersive X-ray spectroscopy（EDX）.The structure of the surfactant played an important role in the synthesis *** the hydrophobic chain length,the stability,and the amount of surfactant increased the quantity of AgNPs *** surface activity of the synthesized cationic surfactants was determined using surface tension measurements at three different *** synthesized surfactants showed a high tendency toward adsorption and *** the hydrophobic chain length of the synthesized surfactant increased its *** the synthesized cationic surfactants and their nano-form against bacteria and fungi showed that they are highly *** silver nanoparticles enhanced the biological activity of the synthesized cationic surfactants.

关键词： Cationic surfactant Silver nanoparticles Dynamic light scattering Biological activity Surface parameters Thermodynamic parameters

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