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Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

Computer systems science & Engineering 2023年第6期45卷 2885-2899页

作者： El-sayed M.El-kenawy abdelaziz A.Abdelhamid Fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of system Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LsTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-sutcliffe model eficiency(NsE),mean square error(MsE),root MsE(RMsE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LsTM,bidirectional LsTM(BiLsTM),gated recurrent unit(GRU),and convolutional LsTM(ConvLsTM).It was found that the proposed approach achieved the lowest RMsE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

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Dipper Throated Algorithm for Feature selection and Classification in Electrocardiogram

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Computer systems science & Engineering 2023年第5期45卷 1469-1482页

作者： Doaa sami Khafaga Amel Ali Alhussan abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mohamed saber El-sayed M.El-kenawy Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Communications Engineering Department Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythmia has been classified using a variety of *** of the dynamic nature of electrocardiogram(ECG)data,traditional handcrafted approaches are difficult to execute,making the machine learning(ML)solutions more *** with cardiac arrhythmias can benefit from competent monitoring to save their *** arrhythmia classification and prediction have greatly improved in recent *** are a category of conditions in which the heart's electrical activity is abnormally rapid or *** year,it is one of the main reasons of mortality for both men and women,*** the classification of arrhythmias,this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors(KNN)*** proposed method makes advantage of the UCI repository,which has a 279-attribute high-dimensional cardiac arrhythmia *** proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia *** method of comprehensive arrhythmia classification outperforms earlier methods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram metaheuristics dipper throated algorithm

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High Gain Predictions for Ni-Like Ta Ions

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Chinese Physics Letters 2013年第11期30卷 80-83页

作者： Wessameldin s.abdelaziz A.A.Farrag H.M.Hamed Mai E.Ahmed National Institute of Laser Enhanced sciences Cairo UniversityGizaEgypt Faculty of science Cairo UniversityGizaEgypt Environmental Affairs Agency(EEAA) Egypt

Atomic structure data and effective collision strengths for 1s^(2)2s^(2)2p^(6)3s^(2)3p^(6)3d^(10) and 54 fine-structure levels are contained in the configurations 1s^(2)2s^(2)2p^(6)3s^(2)3p^(6)3d^(9)4l(l=s,p,d,f)for the nickel-like Ta *** data are used in the determination of the reduced population for the 55 fine structure levels over a wide range of electron densities(from 10^(21) to 10^(23))and at various electron plasma *** gain coefficients for those transitions with a positive population inversion factor are determined and plotted against the electron density.

关键词： density nickel structure

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Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

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Computers, Materials & Continua 2023年第2期74卷 2379-2395页

作者： Doaa sami Khafaga El-sayed M.El-kenawy Faten Khalid Karim sameer Alshetewi Abdelhameed Ibrahim abdelaziz A.Abdelhamid D.L.Elsheweikh 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 Department of Computer science Faculty of Specific EducationMansoura UniversityEgypt

Electrocardiogram(ECG)signal is a measure of the heart’s electrical ***,ECG detection and classification have benefited from the use of computer-aided systems by *** goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization(DTO)and Differential Evolution Algorithm(DEA)into a unified algorithm to optimize the hyperparameters of neural network(NN)for boosting the ECG classification *** addition,we proposed a new feature selection method for selecting the significant feature that can improve the overall *** prove the superiority of the proposed approach,several experimentswere conducted to compare the results achieved by the proposed approach and other competing ***,statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA *** results confirmed the superiority and effectiveness of the proposed *** classification accuracy achieved by the proposed approach is(99.98%).

关键词： Electrocardiogram differential evolution algorithm dipper throated optimization neural networks

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Hybrid Dipper Throated and Grey Wolf Optimization for Feature selection Applied to Life Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4531-4545页

作者： Doaa sami Khafaga El-sayed M.El-kenawy Faten Khalid Karim Mostafa Abotaleb Abdelhameed Ibrahim abdelaziz A.Abdelhamid D.L.Elsheweikh 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 Department of system Programming South Ural State UniversityChelyabinsk454080Russia 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 Department of Computer science Faculty of Specific EducationMansoura UniversityEgypt

selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PsO),bPsO,binary stochastic fractal search(bsFs),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bsBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.

关键词： Metaheuristics dipper throated optimization grey wolf optimization binary optimizer feature selection

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Fuzzy Genetic sharing for Dynamic Optimization

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International Journal of Automation and computing 2012年第6期9卷 616-626页

作者： Khalid Jebari abdelaziz Bouroumi Aziz Ettouhami Conception and systems Laboratory Faculty of SciencesMohammed V-Agdal University Modeling and Instrumentation Laboratory Ben Msik Faculty of SciencesHassan II Mohammedia-Casablanca University

Recently,genetic algorithms(GAs) have been applied to multi-modal dynamic optimization(MDO).In this kind of optimization,an algorithm is required not only to find the multiple optimal solutions but also to locate a dynamically changing *** fuzzy genetic sharing(FGs) approach is based on a novel genetic algorithm with dynamic niche sharing(GADNs).FGs finds the optimal solutions,while maintaining the diversity of the *** this,FGs uses several ***,an unsupervised fuzzy clustering method is used to track multiple optima and perform ***,a modified tournament selection is used to control selection ***,a novel mutation with an adaptive mutation rate is used to locate unexplored search *** effectiveness of FGs in dynamic environments is demonstrated using the generalized dynamic benchmark generator(GDBG).

关键词： Genetic algorithms unsupervised learning fuzzy clustering dynamic optimization evolutionary algorithms dynamic niche sharing Hill s diversity index multi-modal function optimization.

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa sami Khafaga El-sayed M.El-kenawy abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia 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 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 Computer science University of Engineering and TechnologyTaxilaPakistan Department of system Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDs)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LsH-sMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDs for three cases,namely,detection without dataset balancing,detection with sMOTE balancing,and detection with the proposed optimized LsHsOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDs17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing sMOTE

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa sami Khafaga Faten Khalid Karim abdelaziz A.Abdelhamid El-sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LsH)and synthetic Minority Oversampling Technique(sMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Metformin alleviates LTA-induced inflammatory response through PPARγ/MAPK/NF-κB signaling pathway in bovine mammary epithelial cells

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BIOCELL 2022年第11期46卷 2443-2454页

作者： abdelaziz ADAM IDRIss ARBAB CHUNQING YIN XUBIN LU YAN LIANG IsMAIL MOHAMED ABDALLA AMER ADAM IDRIs TIANLE XU YONGJIANG MAO ZHANGPING YANG College of Animal science and Technology Yangzhou UniversityYangzhou225009China Joint International Research Laboratory of Agriculture and Agri-Product safety ofMinistry of Education of China Yangzhou UniversityYangzhou225009China Biomedical Research Institute Darfur CollegeNyala63313Sudan shandong Haiding husbandry Co. Ltd.Jinan250100China

Mastitis is a common inflammatory cow mammary infection;that causes significant economic loss in dairy *** the interesting connection between metformin’s anti-inflammatory function and mastitis model induced by LTA in pbMECs,our objective was to prove that metformin was beneficial in suppressing proinflammatory response induced by LTA through modulation of mitogen-activated protein kinase(MAPK)and nuclear factor kappa B(NF-κB)signaling pathways and activation of peroxisome proliferator-activated receptor-γ(PPARγ)in *** proliferation of cells and mRNA expression were measured using EdU assay and quantitative reverse transcriptase-polymerase chain reaction(qRT-PCR).Immunoblotting and immunofluorescence analysis were conducted to evaluate the expression of target proteins in inflammatory and anti-inflammatory responses to metformin and ***,pbMECs were allowed to treat with the PPAR antagonist GW9662,and inflammatory markers were detected in the *** results showed that LTA concentration at 100μg/mL significantly stimulated the MAPK14,IL-6 and IL-1βmRNA expressions compared to the control cells(Pse-dependent tests for *** suppressed the phosphorylation expressions of MAPK(ERK1/2,p38,and JNK)in LTA-stimulated *** also reduced the protein expression of NF-κB,interleukin-8(IL-8),interleukin-1β(IL-1β)and interleukin-6(IL-6)in pbMECs pretreated with *** administration activated PPARγphosphorylation by up-regulating the expression of PPARγin LTA-stimulated *** with GW9662 resulted in increased IL-6 expression,which was reversed by *** findings collectively indicated that metformin act to attenuate LTA-stimulated inflammatory response in pbMECs by suppressing MAPK and NF-κB activation via a mechanism partially dependent on PPARγ*** results suggested that metformin could function as an anti-inflammatory drug in the treatment of mastitis.

关键词： Metformin LTA Primary bovine mammary epithelial cell Anti-inflammatory effect PPARγ Nuclear factor-κB Mitogen-activated protein kinase

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Adaptive Fuzzy sliding Mode Power system stabilizer Using Nussbaum Gain

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International Journal of Automation and computing 2013年第4期10卷 281-287页

作者： Emira Nechadi Mohamed Naguib Harmas Najib Essounbouli abdelaziz Hamzaoui Electrical Engineering Department Ferhat Abbas University of Stif 1 Centre of Research for science and Information Technology and Communication Laboratory Champagne Ardennes University

Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus （sMIB） and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.

关键词： Multi-machine power system stabilizer adaptive fuzzy sliding mode Nussbaum gain Lyapounov stability.

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