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Parameter Tuned machine Learning Based Emotion Recognition on Arabic Twitter Data

Computer Systems Science & Engineering 2023年第9期46卷 3423-3438页

作者： Ibrahim m.Alwayle Badriyya B.Al-onazi Jaber S.Alzahrani khaled m.alalayah Khadija m.Alaidarous Ibrahim Abdulrab Ahmed mahmoud Othman Abdelwahed motwakel Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajran55461Saudi Arabia 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 UniversityNajran24211Saudi Arabia Computer Department Applied CollegeNajran UniversityNajran66462Saudi 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

Arabic is one of the most spoken languages across the ***,there are fewer studies concerning Sentiment Analysis(SA)in *** recent years,the detected sentiments and emotions expressed in tweets have received significant *** substantial role played by the Arab region in international politics and the global economy has urged the need to examine the sentiments and emotions in the Arabic *** common models are available:machine Learning and lexicon-based approaches to address emotion classification *** this motivation,the current research article develops a Teaching and Learning Optimization with machine Learning Based Emotion Recognition and Classification(TLBOmL-ERC)model for Sentiment Analysis on tweets made in the Arabic *** presented TLBOmL-ERC model focuses on recognising emotions and sentiments expressed in Arabic *** attain this,the proposed TLBOmLERC model initially carries out data pre-processing and a Continuous Bag Of Words(CBOW)-based word embedding *** addition,Denoising Autoencoder(DAE)model is also exploited to categorise different emotions expressed in Arabic *** improve the efficacy of the DAE model,the Teaching and Learning-based Optimization(TLBO)algorithm is utilized to optimize the *** proposed TLBOmL-ERC method was experimentally validated with the help of an Arabic tweets *** obtained results show the promising performance of the proposed TLBOmL-ERC model on Arabic emotion classification.

关键词： Arabic language Twitter data machine learning teaching and learning-based optimization sentiment analysis emotion classification

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Learning-Based Artificial Algae Algorithm with Optimal machine Learning Enabled malware Detection

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Computer Systems Science & Engineering 2023年第9期46卷 3103-3119页

作者： khaled m.alalayah Fatma S.Alrayes mohamed K.Nour Khadija m.Alaidarous Ibrahim m.Alwayle Heba mohsen Ibrahim Abdulrab Ahmed mesfer Al Duhayyim Department of Computer Science College of Science and ArtsNajran UniversitySharurahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess 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 Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and *** malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,*** is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of *** prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with machine Learning(mL)*** study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal machine Learning Enabled malware Detection(LBAAA-OmLmD)approach in Computer *** presented LBAAA-OmLmDmodelmainly aims to detect and classify the existence of ransomware and goodware in the *** accomplish this,the LBAAA-OmLmD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality ***,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is *** FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier *** experimental validation of the LBAAA-OmLmD model is tested using a benchmark dataset,and the outcomes are inspected in distinct *** comprehensive comparative examination demonstrated the betterment of the LBAAAOmLmD model over recent algorithms.

关键词： Computer networks machine learning security malware detection feature selection ransomware

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Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

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Computer Systems Science & Engineering 2023年第9期46卷 3121-3139页

作者： khaled m.alalayah Fatma S.Alrayes Jaber S.Alzahrani Khadija m.Alaidarous Ibrahim m.Alwayle Heba mohsen Ibrahim Abdulrab Ahmed mesfer Al Duhayyim Department of Computer Science College of Science and ArtsSharurahNajran UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

With the increased advancements of smart industries,cybersecurity has become a vital growth factor in the success of industrial *** Industrial Internet of Things(IIoT)or Industry 4.0 has revolutionized the concepts of manufacturing and production *** industry 4.0,powerful IntrusionDetection Systems(IDS)play a significant role in ensuring network *** various intrusion detection techniques have been developed so far,it is challenging to protect the intricate data of *** is because conventional machine Learning(mL)approaches are inadequate and insufficient to address the demands of dynamic IIoT ***,the existing Deep Learning(DL)can be employed to identify anonymous ***,the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection(HGSODLID)model for the IIoT *** presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful *** HGSO algorithm is employed for Feature Selection(HGSO-FS)to reduce the curse of ***,Sparrow Search Optimization(SSO)is utilized with a Graph Convolutional Network(GCN)to classify and identify intrusions in the ***,the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN *** proposed HGSODL-ID model was experimentally validated using a benchmark dataset,and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.

关键词： Industrial IoT deep learning network security intrusion detection system attribute selection smart factory

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Automated Spam Review Detection Using Hybrid Deep Learning on Arabic Opinions

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Computer Systems Science & Engineering 2023年第9期46卷 2947-2961页

作者： Ibrahimm.Alwayle Badriyya B.Al-onazi mohamed K.Nour khaled m.alalayah Khadija m.Alaidarous Ibrahim Abdulrab Ahmed Amal S.mehanna Abdelwahed motwakel Department of Computer Science College of Science and ArtsSharurahNajran UniversitySaudi Arabia 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 Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Online reviews regarding purchasing services or products offered are the main source of users’*** gain fame or profit,generally,spam reviews are written to demote or promote certain targeted products or *** practice is called review *** the last few years,various techniques have been recommended to solve the problem of spam *** spam detection study focuses on English reviews,with a lesser interest in other *** review detection in Arabic online sources is an innovative topic despite the vast amount of data ***,this study develops an Automated Spam Review Detection using optimal Stacked Gated Recurrent Unit(SRD-OSGRU)on Arabic Opinion *** presented SRD-OSGRU model mainly intends to classify Arabic reviews into two classes:spam and ***,the presented SRD-OSGRU model follows different levels of data preprocessing to convert the actual review data into a compatible ***,unigram and bigram feature extractors are *** SGRU model is employed in this study to identify and classify Arabic spam *** the trial-and-error adjustment of hyperparameters is a tedious process,a white shark optimizer(WSO)is utilized,boosting the detection efficiency of the SGRU *** experimental validation of the SRD-OSGRU model is assessed under two datasets,namely DOSC *** extensive comparison study pointed out the enhanced performance of the SRD-OSGRU model over other recent approaches.

关键词： Arabic text spam reviews machine learning deep learning white shark optimizer

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Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

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Intelligent Automation & Soft Computing 2023年第11期38卷 153-168页

作者： Ibrahim m.Alwayle Hala J.Alshahrani Saud S.Alotaibi khaled m.alalayah Amira Sayed A.Aziz Khadija m.Alaidarous Ibrahim Abdulrab Ahmed manar Ahmed Hamza Department of Computer Science College of Science and ArtsSharurahNajran UniversitySharurahSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversityMakkahSaudi Arabia Department of Digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

ive Arabic Text Summarization using Hyperparameter Tuned Denoising Deep Neural Network(AATS-HTDDNN)*** presented AATS-HTDDNN technique aims to generate summaries of Arabic *** the presented AATS-HTDDNN technique,the DDNN model is utilized to generate the *** study exploits the Chameleon Swarm Optimization(CSO)algorithm to fine-tune the hyperparameters relevant to the DDNN model since it considerably affects the summarization *** phase shows the novelty of the current *** validate the enhanced summarization performance of the proposed AATS-HTDDNN model,a comprehensive experimental analysis was *** comparison study outcomes confirmed the better performance of the AATS-HTDDNN model over other approaches.

关键词： Text summarization deep learning denoising deep neural networks hyperparameter tuning Arabic language

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Robust malicious Executable Detection Using Host-Based machine Learning Classifier

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Computers, materials & Continua 2024年第4期79卷 1419-1439页

作者： khaled Soliman mohamed Sobh Ayman m.Bahaa-Eldin Department of Computer and Systems Engineering Ain Shams UniversityCairo11517Egypt Department of Computer Engineering Technology ElSewedy University of TechnologyCairo44629Egypt

The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust malicious ExecutableDetection (RmED) using Host-based machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RmED *** most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RmED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.

关键词： Portable executable malware intrusion detection cybersecurity zero-day threats Host IntrusionDetection System(HIDS) machine learning Anomaly-based Intrusion Detection System(AIDS) deep learning

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Calculus bovis in hepatocellular carcinoma:Tumor molecular basis,Wnt/β-catenin pathway role,and protective mechanism

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World Journal of Gastroenterology 2024年第35期30卷 3959-3964页

作者： khaled mohamed mohamed Koriem Department of medical Physiology Medical Research and Clinical Studies InstituteNational Research CentreGiza 12622Egypt

In this editorial,we comment on the recent article by Huang et *** editorial focuses specifically on the molecular mechanisms of hepatocellular carcinoma(HCC),mechanism of Wnt/β-catenin pathway in HCC,and protective mechanism of Calculus bovis(CB)in *** cancer is the fourth most common cause of cancer-related deaths *** most prevalent kind of primary liver cancer,HCC,is typically brought on by long-term viral infections(hepatitis B and C),non-alcoholic steatohepatitis,excessive alcohol consumption,and other conditions that can cause the liver to become chronically inflamed and *** is a wellknown traditional remedy in China and Japan and has been used extensively to treat a variety of diseases,such as high fever,convulsions,and *** in lipid metabolism,cholesterol metabolism,bile acid metabolism,alcohol metabolism,and xenobiotic detoxification lead to fatty liver disease and liver ***,which is a tricarboxylic acid cycle intermediate,is vital to energy production and mitochondrial *** is also thought to be a signaling molecule in metabolism and in the development and spread of liver *** Wnt/β-catenin pathway is made up of a group of proteins that are essential for both adult tissue homeostasis and embryonic *** is frequently caused by the dysregulation of the Wnt/β-catenin signaling *** HCC liver carcinogenesis,Wnt/β-catenin signaling is activated by the expression of downstream target *** between the liver and the gut exists via the portal vein,biliary tract,and systemic ***"gutliver axis"controls intestinal *** of the main factors contributing to the development,progression,and treatment resistance of HCC is the abnormal activation of the Wnt/β-Catenin signaling ***,understanding this pathway is essential to treating *** ingredients of CB,particularly oleanolic acid,ergosterol,and ursolic acid,have anti-p

关键词： Hepatocellular carcinoma microRNAs Wnt/β-catenin pathway Calculus bovis Apoptosis

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Comparative analysis on the performance of different types of input-and command-shaping controllers in minimizing payload residual vibration of an overhead crane with an inclined supporting track

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International Journal of mechanical System Dynamics 2024年第1期4卷 22-33页

作者： mohammed Alfares khaled Alhazza mechanical Engineering Department College of Engineering and PetroleumKuwait UniversityKuwait CityKuwait

Reducing the effects of external disturbance on overhead crane systems is crucial,as they can impair the controller performance and cause excessive vibrations or oscillations of the *** such external disturbance is the inclination of the supporting track of the crane trolley,which causes the system dynamics model to *** open-loop control strategy is widely utilized to control the payload sway motion and generally does not require any alterations in the physical structure of a system or the installation of sensors and/or *** and command shaping are two common open-loop control techniques applied to control overhead *** this paper,the effect of moving an overhead crane system along an inclined supporting track is *** addition,the ability of different types of input-and command-shaping control schemes to suppress the residual vibrations due to trolley track inclination is *** types of input-shaping controllers,which are double-step,zero vibration,and one command waveform(WF)shaper based on a trigonometric function,are used and tested.A linear equation of motion of the overhead crane resting on an inclined surface is developed to simulate the overhead crane and payload *** effectiveness of the different types of open-loop controllers to suppress residual vibrations is verified by both simulation and experimental *** addition,a new WF command shaper is proposed and designed to overcome track inclination while eliminating payload residual vibration.A comprehensive comparative analysis,both numerically and experimentally,is performed on the new proposed shaper to measure its effectiveness in handling inclination when compared to other types of open-loop *** new shaper outperforms other controllers in eliminating payload residual vibration for a wider range of inclination angles.

关键词： overhead cranes open-loop control input and command shaping payload residual vibrations

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magneto-Photo-Thermoelastic Excitation Rotating Semiconductor medium Based on moisture Diffusivity

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Computer modeling in Engineering & Sciences 2024年第10期141卷 107-126页

作者： khaled Lotfy A.m.S.mahdy Alaa A.El-Bary E.S.Elidy Department of mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Department of mathematics Faculty of ScienceTaibah UniversityMadinah42353Saudi Arabia Department of mathematics and Statistics College of ScienceTaif UniversityTaif11099Saudi Arabia Arab Academy for Science Technology and Maritime TransportAlexandria1029Egypt

In this research,we focus on the free-surface deformation of a one-dimensional elastic semiconductor medium as a function of magnetic field and moisture *** problem aims to analyze the interconnection between plasma and moisture diffusivity processes,as well as thermo-elastic *** study examines the photothermoelasticity transport process while considering the impact of moisture *** employing Laplace’s transformation technique,we derive the governing equations of the photo-thermo-elastic *** equations include the equations for carrier density,elastic waves,moisture transport,heat conduction,and constitutive *** stresses,thermal conditions,and plasma boundary conditions are used to calculate the fundamental physical parameters in the Laplace *** employing numerical techniques,the Laplace transform is inverted to get complete time-domain solutions for the primary physical domains under ***,thermoelastic,and thermoelectric characteristics are employed in conjunction with a graphical analysis that takes into consideration the effects of applied forces on displacement,moisture concentration,carrier density,stress due to forces,and temperature distribution.

关键词： moisture diffusivity semiconductor photothermoelastic rotation thermomechanical waves laplace transform

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A review of mechanism of action of outdoor exposure in preventing myopia incidence and progression

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International Journal of Ophthalmology(English edition) 2024年第6期17卷 1144-1155页

作者： Chikezie Grand Ihesiulor khaled Alzahrani Hema Rhadhakrishnan Division of Pharmacy&Optometry School of Health SciencesFaculty of BiologyMedicine and HealthThe University of ManchesterManchester M139PLUnited Kingdom Department of Ophthalmology King Fahad Armed Forces HospitalJeddah 23311Saudi Arabia

Various studies have suggested several environmental,pharmacological,medical,and optical interventions and some are in use but their efficacy in myopia control may be transient,and the cellular,molecular,and biochemical mechanisms involved *** exposure is currently regarded as an effective and enduring strategy in the control of myopia development and ***,the mechanism behind the effect of outdoor exposure and its association with genetic predisposition and other relatively more significant environmental factors on myopia is still a *** review focuses on survey-based and intervention-based studies carried out to propose a mechanism that accounts for myopia development and important for its control.

关键词： outdoor exposure daylight exposure myopia control myopia

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