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Modified Dragonfly Optimization with Machine Learning Based Arabic Text Recognition

Computers, Materials & Continua 2023年第8期76卷 1537-1554页

作者： Badriyya BAl-onazi Najm Alotaibi Jaber SAlzahrani Hussain Alshahrani mohamed ahmed elfaki Radwa Marzouk Mahmoud Othman Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Text classification or categorization is the procedure of automatically tagging a textual document with most related labels or *** the number of labels is limited to one,the task becomes single-label text *** Arabic texts include unstructured information also like English texts,and that is understandable for machine learning(ML)techniques,the text is changed and demonstrated by numerical *** recent times,the dominant method for natural language processing(NLP)tasks is recurrent neural network(RNN),in general,long short termmemory(LSTM)and convolutional neural network(CNN).Deep learning(DL)models are currently presented for deriving a massive amount of text deep features to an optimum performance from distinct domains such as text detection,medical image analysis,and so *** paper introduces aModified Dragonfly Optimization with Extreme Learning Machine for Text Representation and Recognition(MDFO-EMTRR)model *** presentedMDFO-EMTRR technique mainly concentrates on the recognition and classification of the Arabic *** achieve this,theMDFO-EMTRRtechnique encompasses data pre-processing to transform the input data into compatible ***,the ELM model is utilized for the representation and recognition of the Arabic *** last,the MDFO algorithm was exploited for optimal tuning of the parameters related to the ELM method and thereby accomplish enhanced classifier *** experimental result analysis of the MDFO-EMTRR system was performed on benchmark datasets and attained maximum accuracy of 99.74%.

关键词： Arabic corpus dragonfly algorithm machine learning text mining extreme learning machine

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The Scientific Revolution in Power Plants

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Smart Grid and Renewable Energy 2012年第2期3卷 96-103页

作者： mohamed Hyder Seid-ahmed elfaki Abu Halima (Block 1 No. 303) Khartoum Sudan

It has been made a proposal of new ideal cycle for power plants which is working by a turbine gas, for both closed and open systems. It has been designed a special device for adding heat at constant volume. The aim of special device is to decrease the amount of added heat for the new cycle. We have made a comparison between the simple gas turbine cycle & the new cycle. The results has been shown, that the efficiency of new cycle is greater than the simple cycle of gas turbine.

关键词： I C (Internal Combustion) E.C (External Combustion) S.C (Simple Gas Turbine Cycle) N.C (New Cycle)

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Arabic Sign Language Gesture Classification Using Deer Hunting Optimization with Machine Learning Model

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Computers, Materials & Continua 2023年第5期75卷 3413-3429页

作者： Badriyya B.Al-onazi mohamed K.Nour Hussain Alshahran mohamed ahmed elfaki Mrim M.Alnfiai Radwa Marzouk Mahmoud Othman Mahir M.Sharif Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science Faculty of Computer Science and Information TechnologyOmdurman Islamic UniversityOmdurman14415Sudan Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sign language includes the motion of the arms and hands to communicate with people with hearing *** models have been available in the literature for sign language detection and classification for enhanced *** the latest advancements in computer vision enable us to perform signs/gesture recognition using deep neural *** paper introduces an Arabic Sign Language Gesture Classification using Deer Hunting Optimization with Machine Learning(ASLGC-DHOML)*** presented ASLGC-DHOML technique mainly concentrates on recognising and classifying sign language *** presented ASLGC-DHOML model primarily pre-processes the input gesture images and generates feature vectors using the densely connected network(DenseNet169)*** gesture recognition and classification,a multilayer perceptron(MLP)classifier is exploited to recognize and classify the existence of sign language ***,the DHO algorithm is utilized for parameter optimization of the MLP *** experimental results of the ASLGC-DHOML model are tested and the outcomes are inspected under distinct *** comparison analysis highlighted that the ASLGC-DHOML method has resulted in enhanced gesture classification results than other techniques with maximum accuracy of 92.88%.

关键词： Machine learning sign language recognition multilayer perceptron deer hunting optimization densenet

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Multi-Versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis on Arabic Corpus

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Computer Systems Science & Engineering 2023年第12期47卷 3049-3065页

作者： Mesfer Al Duhayyim Badriyya B.Al-onazi Jaber S.Alzahrani Hussain Alshahrani mohamed ahmed elfaki Abdullah mohamed Ishfaq Yaseen Gouse Pasha Mohammed Mohammed Rizwanullah Abu Sarwar Zamani Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAflaj16273Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sentiment analysis(SA)of the Arabic language becomes important despite scarce annotated corpora and confined *** affect Analysis has become an active research zone *** still,the Arabic language lags behind adequate language sources for enabling the SA ***,Arabic still faces challenges in natural language processing(NLP)tasks because of its structure complexities,history,and distinct *** has gained lesser effort than the other *** paper developed a Multi-versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis(MVODRL-AA)on Arabic *** presented MVODRL-AAmodelmajorly concentrates on identifying and classifying effects or emotions that occurred in the Arabic ***,the MVODRL-AA model follows data pre-processing and word ***,an n-gram model is utilized to generate word embeddings.A deep Q-learning network(DQLN)model is then exploited to identify and classify the effect on the Arabic *** last,the MVO algorithm is used as a hyperparameter tuning approach to adjust the hyperparameters related to the DQLN model,showing the novelty of the work.A series of simulations were carried out to exhibit the promising performance of the MVODRL-AA *** simulation outcomes illustrate the betterment of the MVODRL-AA method over the other approaches with an accuracy of 99.27%.

关键词： Arabic language Arabic corpus natural language processing affect analysis deep learning

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Chaotic Elephant Herd Optimization with Machine Learning for Arabic Hate Speech Detection

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Intelligent Automation & Soft Computing 2024年第3期39卷 567-583页

作者： Badriyya B.Al-onazi Jaber S.Alzahrani Najm Alotaibi Hussain Alshahrani mohamed ahmed elfaki Radwa Marzouk Heba Mohsen Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh12735Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqra11911Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in Egypt New CairoNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipAl-Kharj16278Saudi Arabia

In recent years,the usage of social networking sites has considerably increased in the Arab *** has empowered individuals to express their opinions,especially in ***,various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different *** is attributed to business owners’understanding of social media’s importance for business ***,the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and *** speech over online social networking sites turns out to be a worldwide issue that reduces the cohesion of civil *** this background,the current study develops a Chaotic Elephant Herd Optimization with Machine Learning for Hate Speech Detection(CEHOML-HSD)model in the context of the Arabic *** presented CEHOML-HSD model majorly concentrates on identifying and categorising the Arabic text into hate speech and *** attain this,the CEHOML-HSD model follows different sub-processes as discussed *** the initial stage,the CEHOML-HSD model undergoes data pre-processing with the help of the TF-IDF ***,the Support Vector Machine(SVM)model is utilized to detect and classify the hate speech texts made in the Arabic ***,the CEHO approach is employed for fine-tuning the parameters involved in *** CEHO approach is developed by combining the chaotic functions with the classical EHO *** design of the CEHO algorithm for parameter tuning shows the novelty of the work.A widespread experimental analysis was executed to validate the enhanced performance of the proposed CEHOML-HSD *** comparative study outcomes established the supremacy of the proposed CEHOML-HSD model over other approaches.

关键词： Arabic language machine learning elephant herd optimization TF-IDF vectorizer hate speech detection

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Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

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Structural Durability & Health Monitoring 2025年第1期19卷 77-103页

作者： Sabrina Meddah Sid ahmed Tadjer Abdelhakim Idir Kong Fah Tee mohamed Zinelabidine Doghmane Madjid Kidouche Applied Automation Laboratory Faculty of Hydrocarbons and ChemistryUniversity of BoumerdesBoumerdes35000Algeria Institute of Electrical and Electronic Engineering(IGEE) University of BoumerdesBoumerdes35000Algeria Laboratory of the Electrification of Industrial Enterprises University of BoumerdesBoumerdes35000Algeria Electrical Engineering Department Mohamed Boudiaf University of M’silaM’sila28000Algeria Department of Civil and Environmental Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Construction and Building Materials King Fahd University of Petroleum&Minerals(KFUPM)Dhahran31261Saudi Arabia

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and *** achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is *** study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling *** study speciﬁcally investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency *** events not only hinder the efﬁciency of drilling but also lead to exhaustion and harm to the system’s components since they are difﬁcult to be detected and controlled in real *** study investigates the dynamic interactions of these vibrations,speciﬁcally in their high-frequency modes,usingﬁeld data obtained from measurement while ***ﬁndings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem *** obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control ***,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect ***,by exploiting theseﬁndings,the assessment of structural resilience in rotary drilling systems can be ***,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efﬁciency of rotary drilling systems in the petroleum industry.

关键词： Rotary drilling systems mechanical vibrations structural durability dynamic interaction analysis ﬁeld data analysis

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Ecological risk assessment of surficial sediment by heavy metals from a submerged archaeology harbor,South Mediterranean Sea,Egypt

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Acta Geochimica 2020年第2期39卷 226-235页

作者： Maha ahmed mohamed Abdallah ahmed mohamed Badr-ElDin Marine Pollution Lab National Institute of Oceanography and FisheriesAlexandriaEgypt Oceanography Department Faculty of ScienceAlexandria UniversityAlexandriaEgypt

A protected semi-enclosed embayment,the Eastern Harbor(EH),is situated in the central sector of the Mediterranean coast of Alexandria,*** is a famous fishing dock and water-sport center and its importance arose after the discovery of the Ptolemaic royal quarter of ancient *** protect this national treasure and improve its environmental health,the untreated anthropogenic effluents,which continued for decades into the EH since 1992,must be totally ***,it is an important issue to continually monitor and asses the environmental status of the *** sediment texture,total organic carbon,and the accumulation,distribution,and ecological risks of Cd,Cr,Pb,As,Hg and A1 were determined with a total of 14 surficial sediments samples collected in the EH during *** contents were compared to the literature data to assess the pollution status of *** factors,Degree of contamination(mCd)and potential ecological risk were calculated as a criterion of possible *** mCd calculation produces an overall average value for a range of pollutants,in the present study the contamination factor that provides a measure of the degree of overall contamination in the surface layers in a particular sampling site may provide a better indication of the state of pollution in the EH sediments than other indicators.

关键词： Heavy metals Eastern harbor Enrichment factors Degree of contamination Potential ecological risk

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Static and dynamic stability responses of multilayer functionally graded carbon nanotubes reinforced composite nanoplates via quasi 3D nonlocal strain gradient theory

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Defence Technology（防务技术） 2022年第10期18卷 1778-1809页

作者： ahmed Amine Daikh mohamed Sid ahmed Houari mohamed Ouejdi Belarbi Salwa A.mohamed mohamed A.Eltaher Laboratoire D'Etude des Structures et de Mecanique des Materiaux Departement de Genie CivilFacultedes Sciences et de La TechnologieUniversite Mustapha Stambouli B.P.305R.P.29000MascaraAlgeria Laboratoire de Genie Energetique et Materiaux LGEMUniversite de BiskraB.P.145R.P07000BiskraAlgeria Department of Engineering Mathematics Zagazig UniversityP.O.Box 44519ZagazigEgypt Faculty of Engineering Mechanical Engineering DepartmentKing Abdulaziz UniversityP.O.Box 80204JeddahSaudi Arabia Faculty of Engineering Mechanical Design and Production DepartmentZagazig UniversityP.O.Box 44519ZagazigEgypt

This manuscript presents the comprehensive study of thickness stretching effects on the free vibration,static stability and bending of multilayer functionally graded(FG)carbon nanotubes reinforced composite(CNTRC)*** nanoscale and microstructure influences are considered through a modified nonlocal strain gradient continuum *** on power-law functions,four different patterns of CNTs distribution are considered in this analysis,a uniform distribution UD,FG-V CNTRC,FG-X CNTRC,and FG-O CNTRC.A 3D kinematic shear deformation theory is proposed to include the stretching influence,which is neglected in classical ***'s principle is applied to derive the governing equations of motion and associated boundary *** solutions are developed based on Galerkin method to solve the governing equilibrium equations based on the generalized higher-order shear deformation theory and the nonlocal strain gradient theory and get the static bending,buckling loads,and natural frequencies of *** with previous works is presented.A detailed parametric analysis is carried out to highlight the impact of thickness stretching,length scale parameter(nonlocal),material scale parameter(gradient),CNTs distribution pattern,geometry of the plate,various boundary conditions and the total number of layers on the stresses,deformation,critical buckling loads and vibration *** new results are also reported in the current study,which will serve as a benchmark for future research.

关键词： 3D shear deformation theory Free vibration Buckling Bending Galerkin method Functionally graded nanotube Nonlocal strain gradient theory

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Friction and wear of sand-contaminated lubricated sliding

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Friction 2018年第4期6卷 457-463页

作者： mohamed ahmed RAMADAN Faculty of Engineering at Helwan Helwan University

This paper reports a test investigation of friction and wear responses from sand contaminated lubricated sliding. The influence of sand contaminants on wear and friction is characterized. Analyses are completed utilizing segments of piston ring sliding against the cylinder liner. Paraffin oil, with and without sand contaminants, is utilized. The effects of the concentration and particle size of sand are examined. Based on the observations in the present work, we found that friction and wear increase with sand concentration in the lube. Solid proposals ought to be considered, in order to enlighten the general population on the importance of changing a car engine's oil filter regularly.

关键词： sand contamination lubrication oil abrasive wear lubricated sliding

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Magnetoresistive properties of Ni-doped La_(0.7)Sr_(0.3)MnO_3 manganites

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Rare Metals 2016年第7期35卷 551-558页

作者： ahmed mohamed ahmed Abd El-Moez ahmed mohamed Medhat Abdelrady Abdellateef Hassan ahmed Abd El-Ghanny Physics Department Faculty of ScienceSohag University

Lao.7Sr0.3Mnl_xNixO3 （x = 0, 0.025, 0.050 and 0.075） ceramics were prepared by the conventional solid-state reaction method. The partial substitution of Mn by Ni2＋ leads to a decrease in cell volume as well as a structural transition from the rhombohedral to the orthorhombic structure. Ni2＋ doping increases the electrical resistivity, decreases the semiconductor-metal transition temperature （Tms） and relatively enhances the room temperature magnetoresistance （MR）, especially in x = 0.025 and around Tins. With respect to conduction mechanism, the small polaron hopping （SPH） and the variable range hopping （VRH） models were used to ex- amine conduction in the semiconducting region.

关键词： Manganites X-ray diffraction Structure Electrical resistivity Magnetoresistance

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