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

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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Facial Expression Recognition Model Depending on Optimized Support Vector Machine

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Computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan Fatma M.Talaat El-Sayed M.El-kenawy abdelaziz A.Abdelhamid Abdelhameed ibrahim Doaa Sami Khafaga Mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

in computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is feasible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(FERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(FERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** FERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,fear,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%F1 score.

关键词： Facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

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identification of an extracellular infection-induced glyceraldehyde-3-phosphate dehydrogenase of the phytopathogenic proteobacterium <i>Pseudomonas syringae</i>pv tomato DC3000

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Advances in Bioscience and Biotechnology 2014年第3期5卷 201-208页

作者： Bouchra Elkhalfi Aurelio Serrano abdelaziz Soukri institute for Plant Biochemistry and Photosynthesis (iBVF) CSIC-Universidad de Sevilla Seville Spain Laboratory of Physiology & Genetics Molecular Faculty of Sci-ences Ain Chock Casablanca Morocco

According to molecular biology, genomic and proteomic data, the phytopathogenic gamma-proteobacterium Pseudomonas syringae pv. tomato DC3000 produces a number of proteins that may promote infection and draw nutrients from plants. Remarkably, P. syringae DC3000 strain possesses three paralogous gap genes encoding glyceraldehyde-3-phosphate dehydrogenase (GAPDH) enzymes with different predicted molecular sizes and metabolic functions. As GAPDH was shown to be a virulence factor in other microbial pathogens, in the current study, we analyzed the expression levels of each paralogous gap gene by realtime PCR to understand the actual impact of their protein products on P. syringae virulence. We found that all of them were strongly induced during the infection process. Nevertheless, proteomic analysis of culture supernatants revealed that only Class i GAPDH1 encoded by the gap1 gene was identified as an extracellular protein in infective cells. These results strongly suggest that this GAPDH should play a role in the infective process, including its well-know enzymatic function in the glycolytic metabolic pathway.

关键词： GAPDH Secretome MALDi-TOF Gene Expression infective State Bacterial Speak RNA

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The Effect of Temperature and Doping Level on the Characteristics of Piezoresistive Pressure Sensor

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Journal of Sensor Technology 2014年第2期4卷 59-65页

作者： Beddiaf abdelaziz Kerrour Fouad Salah Kemouche Department of Electronics Faculty of Science and Technology Khenchela University Khenchela Algeria MoDERNa Laboratory University of Constantine 1 Constantine Algeria MoDERNa Laboratory University of Constantine 1 Constantine Algeria

Piezoresistive pressure sensors based on silicon have a large thermal drift because of their high sensitivity to temperature. The study of the effect of the temperature and doping level on characteristics of these sensors is essential to define the parameters that cause the output characteristics drift. in this study, we adopted the model of Kanda to determine the effect of the temperature and of doping level on the piezoresistivity of the Silicon monocrystal. This is to represent P(N,T) and for p-type silicon as functions of impurity concentration for different temperatures. This allows us to see the effect of temperature and doping concentration on the output characteristics of the sensor. Finally, we study the geometric influence parameters and doping on these characteristics to optimize the sensor performance. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

关键词： Thermal Drift Pressure Piezoresistivity Piezoresistive Coefficients Sensor

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Analytical and Numerical Modeling of Flow in a Fractured Gneiss Aquifer

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Journal of Water Resource and Protection 2012年第8期4卷 657-662页

作者： Ramadan abdelaziz Broder J.Merkel Department for Geology Technische Universitat Bergakademie FreibergFreibergGermany

investigating and modeling fluid flow in fractured aquifers is a challenge. This study presents the results of a series of packer tests conducted in a fractured aquifer in Freiberg, Germany, where gneiss is the dominant rock type. Two methods were applied to acquire hydraulic properties from the packer tests: analytical and numerical modeling. MLU (Multi-Layer Unsteady state) for Windows is the analytical model that was applied. ANSYS-FLOTRAN was used to build a two-dimensional numerical model of the geometry of the layered aquifer. A reasonable match between experimental data and simulated data was achieved with the 2D numerical model while the solution from the analytical model revealed significant deviations with respect to direction.

关键词： Ansys/Flotran MLU for Windows Gneiss Packer Test Fractured Aquifer

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The impact of Single Low Dose iV Magnesium Sulphate Adjuvant to Ultrasound Guided Transverses Abdominis Plain Block for Control of Postcesarean Pain

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Open Journal of Obstetrics and Gynecology 2017年第3期7卷 269-280页

作者： Tamer Nabil Abd Elrahman Mohamed abdelaziz Youssry Anesthesia and intensive Care and Pain Department Faculty of Medicine Ain Shams University Cairo Egypt Obstetrics and Gynecology Department Faculty of Medicine Alexandria University Alexandria Egypt

Objective: The aim of this study is to determine the role of preoperative low dose intravenous MgSO4 when given adjuvant to ultrasound guided transversus abdominis plane (TAP) block in augmenting postcesarean analgesic effects and reducing opioid requirements during the first 24 hours. Subjects and Methods: in this prospective, randomized double blind study, a total of sixty full term pregnant women were recruited for the study underwent caesarean section. Thirty patients were assigned to MgSO4 group (A) and another thirty to placebo group (B). Participants in group (A) received 50 mg/kg MgSO4 in 100 ml isotonic saline intravenous (iV) over 20 minutes prior to induction of general anesthesia by 30 minutes while participants in group (B) received 100 ml isotonic saline (placebo) by the same route and over the same duration as control. Results: Visual Analogue Scale (VAS) was analysed within 24 hours postoperatively. The mean pain score at 6 and 12 hours postoperatively was significantly lower in MgSO4 group compared to control group (40.4 ± 5.12 vs 53.6 ± 4.92;26.1 ± 3.01 vs 35.5 ± 3.98 respectively, p = 0.012, 0.005). Comparing both groups regarding the mean time interval of first rescue analgesia (morphine sulphate) requested by the patients, it was longer in MgSO4 group compared to control group. The total dose of rescue analgesia consumed during 24 hours was analysed and it was significantly higher in control group compared to MgSO4 group (10.1 ± 0.95 vs 6.2 ± 0.87, p = 0.001). Conclusion: We concluded that preoperative low doses (50 mg/Kg) of MgSO4 with general anesthesia combined with ultrasound guided TAP block offer longer postoperative pain free periods thus reducing total opioid consumption. in addition to the safety of the drug to the mother and fetus so we recommend iV MgSO4 as an adjuvant therapy with TAP block.

关键词： Transversus Abdominis Plane Block Magnesium Sulphate Postcesarean Analgesia Rescue Analgesia

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Systematic Approach to Compute the Vibrational Energy Levels of Diatomic Molecules

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Journal of Applied Mathematics and Physics 2020年第11期8卷 2463-2474页

作者： Mohammed Janati idrissi abdelaziz Fedoul Salaheddine Sayouri Laboratory of Applied Physics informatics and Statistics Faculty of Sciences Dhar Al Mahraz University of Sidi Mohamed Ben Abdellah Fez Morocco

in continuation of our previous paper of the anharmonic potentials analysis through the Floquet representation, we performed in this work a systematic calculation of the diatomic vibrational energy levels as well as the corresponding wave functions. The solution of Schrödinger equation according to Morse potential, which is a suitable model to describe the diatomic vibrational spectra, has been introduced;thus the explicit formulas to the second order have been established. As an illustration, the dissociation energies of some molecules species (i.e. ScN, LiH, Cl2 and NO) have been computed, as well as the wave functions and the corresponding probability densities, relating to the (ScN) molecule have been represented. Comparisons of our results with those of literature have been made.

关键词： Morse Potential Diatomic Molecule Dissociation Birge-Sponer

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Extended Finite Element Modeling: Basic Review and Programming

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Engineering（科研） 2011年第7期3卷 713-718页

作者： Yazid abdelaziz K. Bendahane A. Baraka 不详

in this work, we have exposed a recent method for modeling crack growth without re-meshing. The main advantage of this method is its capability in modeling discontinuities independently, so the mesh is prepared without any considering the existence of discontinuities. The paper covers the formulation and implementation of XFEM, and discusses various aspects of the approach (enrichments functions, level set representation, numerical integration…). Numerical experiments show the effectiveness and robustness of the XFEM implementation.

关键词： X-FEM Programming Fracture Cracks LSM

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Robust Parametric Modeling of Speech in Additive White Gaussian Noise

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Journal of Signal and information Processing 2015年第2期6卷 99-108页

作者： abdelaziz Trabelsi Otmane Ait Mohamed Yves Audet Department of Electrical and Computer Engineering Concordia University Montréal Canada Department of Electrical Engineering école Polytechnique de Montréal Montréal Canada

in estimating the linear prediction coefficients for an autoregressive spectral model, the concept of using the Yule-Walker equations is often invoked. in case of additive white Gaussian noise (AWGN), a typical parameter compensation method involves using a minimal set of Yule-Walker equation evaluations and removing a noise variance estimate from the principal diagonal of the autocorrelation matrix. Due to a potential over-subtraction of the noise variance, however, this method may not retain the symmetric Toeplitz structure of the autocorrelation matrix and thereby may not guarantee a positive-definite matrix estimate. As a result, a significant decrease in estimation performance may occur. To counteract this problem, a parametric modelling of speech contaminated by AWGN, assuming that the noise variance can be estimated, is herein presented. it is shown that by combining a suitable noise variance estimator with an efficient iterative scheme, a significant improvement in modelling performance can be achieved. The noise variance is estimated from the least squares analysis of an overdetermined set of p lower-order Yule-Walker equations. Simulation results indicate that the proposed method provides better parameter estimates in comparison to the standard Least Mean Squares (LMS) technique which uses a minimal set of evaluations for determining the spectral parameters.

关键词： ARMA Model Noise Variance Overdetermined Parametric Evaluation Singular Value Representation LMS Technique Yule-Walker Equations

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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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