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AMachine Learning Approach to Cyberbullying Detection in Arabic Tweets

Computers, Materials & Continua 2024年第7期80卷 1033-1054页

作者： Dhiaa Musleh Atta Rahman Mohammed Abbas Alkherallah Menhal Kamel Al-Bohassan Mustafa Mohammed Alawami Hayder Ali Alsebaa Jawad Ali Alnemer Ghazi Fayez Al-Mutairi May Issa Aldossary Dalal A.Aldowaihi fahd alhaidari Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Networks and Communications College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

With the rapid growth of internet usage,a new situation has been created that enables practicing *** has increased over the past decade,and it has the same adverse effects as face-to-face bullying,like anger,sadness,anxiety,and *** the anonymity people get on the internet,they tend to bemore aggressive and express their emotions freely without considering the effects,which can be a reason for the increase in cyberbullying and it is the main motive behind the current *** study presents a thorough background of cyberbullying and the techniques used to collect,preprocess,and analyze the ***,a comprehensive review of the literature has been conducted to figure out research gaps and effective techniques and practices in cyberbullying detection in various languages,and it was deduced that there is significant room for improvement in the Arabic *** a result,the current study focuses on the investigation of shortlisted machine learning algorithms in natural language processing(NLP)for the classification of Arabic datasets duly collected from Twitter(also known as X).In this regard,support vector machine(SVM),Naive Bayes(NB),Random Forest(RF),Logistic regression(LR),Bootstrap aggregating(Bagging),Gradient Boosting(GBoost),Light Gradient Boosting Machine(LightGBM),Adaptive Boosting(AdaBoost),and eXtreme Gradient Boosting(XGBoost)were shortlisted and investigated due to their effectiveness in the similar ***,the scheme was evaluated by well-known performance measures like accuracy,precision,Recall,and ***,XGBoost exhibited the best performance with 89.95%accuracy,which is promising compared to the state-of-the-art.

关键词： Supervised machine learning ensemble learning cyberbullying Arabic tweets NLP

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Authenblue: A New Authentication Protocol for the Industrial Internet of Things

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Computers, Materials & Continua 2021年第4期67卷 1103-1119页

作者： Rachid Zagrouba Asayel AlAbdullatif Kholood AlAjaji Norah Al-Serhani fahd alhaidari Abdullah Almuhaideb Atta-ur-Rahman Department of Computer Information System College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

The Internet of Things(IoT)is where almost anything can be controlled and managed remotely by means of *** the IoT evolution led to quality of life enhancement,many of its devices are *** lack of robust key management systems,efficient identity authentication,low fault tolerance,and many other issues lead to IoT devices being easily targeted by *** this paper we propose a new authentication protocol called Authenblue that improve the authentication process of IoT devices and Coordinators of Personal Area Network(CPANs)in an Industrial IoT(IIoT)*** study proposed Authenblue protocol as a new Blockchainbased authentication *** enhance the authentication process and make it more secure,Authenblue modified the way of generating IIoT identifiers and the shared secret keys used by the IIoT devices to raise the efficiency of the authentication *** enhance the authentication protocol that other models rely on by enhancing the approach used to generate the User Identifier(UI).The UI values changed from being static values,sensors MAC addresses,to be generated values in the inception *** approach makes the process of renewing the sensor keys more secure by renewing their UI values instead of changing the secret *** this study,Authenblue has been simulated in the Network Simulator 3(NS3).Simulation results show an improved performance compared to the related work.

关键词： Authentication industrial internet of things security Authenblue blockchain NS3

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Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2289-2327页

作者： Saima Rashid fahd Jarad Department of Mathematics Government College UniversityFaisalabad38000Pakistan Department of Natural Sciences School of Arts and SciencesLebanese American UniversityBeirut11022801Lebanon Department of Mathematics Faculty of Arts and ScienceÇnkaya UniversityAnkara06790Turkey Department of Medical Research China Medical UniversityTaichung40402TaiwanChina

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world *** this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler *** this approach,the overall population was separated into five ***,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity *** included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of *** numerical simulations for various fractional orders and randomization intensities are illustrated.

关键词： Measles epidemic model Atangana-Baleanu Caputo-Fabrizio differential operators existence and uniqueness qualitative analysis Newton interpolating polynomial

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Intelligent Software-Defined Network for Cognitive Routing Optimization Using Deep Extreme Learning Machine Approach

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Computers, Materials & Continua 2021年第4期67卷 1269-1285页

作者： fahd alhaidari Sultan H.Almotiri Mohammed A.Al Ghamdi Muhammad Adnan Khan Abdur Rehman Sagheer Abbas Khalid Masood Khan Atta-ur-Rahman Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science Umm Al-Qura UniversityMakkah City715Saudi Arabia Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science NCBA&ELahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

In recent years,the infrastructure,instruments,and resources of network systems are becoming more complex and heterogeneous,with the rapid development of current internet and mobile communication *** order to efficaciously prepare,control,hold and optimize networking systems,greater intelligence needs to be ***,due to the inherently dispensed characteristic of conventional networks,Machine Learning(ML)techniques are hard to implement and deployed to govern and operate ***-Defined Networking(SDN)brings us new possibilities to offer intelligence in the ***’s characteristics(e.g.,logically centralized control,global network view,software-based site visitor analysis,and dynamic updating of forwarding rules)make it simpler to apply machine learning *** perspectives of fiber-optic communications including fiber nonlinearity coverage,optical performance checking,cognitive shortcoming detection/anticipation,and arranging and improvement of softwaredefined networks are examined in Machine Learning(ML)*** research paper has presented an imaginative framework concept called Intelligent Software Defined Network(ISDN)for Cognitive Routing Optimization(CRO)using Deep Extreme Learning Machine(DELM)approach(ISDN-CRO-DELM)in light of the new challenges in the development and operation of communication systems,and capturing motivation from how living creatures deal with difficulty and *** proposed methodology develops around the planned applications of progressive DELM methods and,specifically,probabilistic generative models for framework wide learning,demonstrating,improvement,and information ***,ISDN-CRO-DELM,suggest to integrate this learning framework with the ISDN for CRO and reconfiguration approaches at the system *** 2019a is used for DELM simulation and superior results show the effectiveness of the proposed framework.

关键词： SDN DELM machine learning cognition

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Automatic Channel Detection Using DNN on 2D Seismic Data

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Computer Systems Science & Engineering 2021年第1期36卷 57-67页

作者： fahd A.alhaidari Saleh A.Al-Dossary Ilyas A.Salih Abdlrhman M.Salem Ahmed S.Bokir Mahmoud O.Fares Mohammed I.Ahmed Mohammed S.Ahmed Imam Abdulrahman Bin Faisal University College of Computer Science and Information TechnologyDammam34212Saudi Arabia Saudi Aramco Oil Company EXPEC-IIDhahranSaudi Arabia

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon *** are among the most important geological features interpreters analyze to locate petroleum ***,manual channel picking is both time consuming and ***,similar to any other process dependent on human intervention,manual channel picking is error prone and *** address these issues,automatic channel detection is both necessary and important for efficient and accurate seismic *** systems make use of real-time image processing techniques for different *** channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil *** this paper,we propose an innovative automatic channel detection algorithm based on machine learning *** new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation *** algorithm uses deep neural network to train the classifier with both the channel and non-channel *** provide a field data example to demonstrate the performance of the new *** training phase gave a maximum accuracy of 84.6%for the classifier and it performed even better in the testing phase,giving a maximum accuracy of 90%.

关键词： Deep neural networks deep learning channel detection image processing two-dimensional seismic data

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A gated recurrent unit model to predict Poisson’s ratio using deep learning

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 123-135页

作者： fahd Saeed Alakbari Mysara Eissa Mohyaldinn Mohammed Abdalla Ayoub Ibnelwaleed A.Hussein Ali Samer Muhsan Syahrir Ridha Abdullah Abduljabbar Salih Petroleum Engineering Department Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia Institute of Hydrocarbon Recovery Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia Gas Processing Center College of EngineeringQatar UniversityP.O.Box 2713DohaQatar Department of Chemical Engineering College of EngineeringQatar UniversityP.O.Box 2713DohaQatar Mechanical Engineering Department Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand *** models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical *** this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error *** GRU model showed the proper trends,and the model data ranges were wider than previous *** GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other *** GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,*** group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

关键词： Static Poisson’s ratio Deep learning Gated recurrent unit(GRU) Sand control Trend analysis Geomechanical properties

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Digital Text Document Watermarking Based Tampering Attack Detection via Internet

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Computer Systems Science & Engineering 2024年第3期48卷 759-771页

作者： Manal Abdullah Alohali Muna Elsadig fahd N.Al-Wesabi Mesfer Al Duhayyim Anwer Mustafa Hilal Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62217Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16733Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Owing to the rapid increase in the interchange of text information through internet networks,the reliability and security of digital content are becoming a major research *** detection,Content authentication,and integrity verification of digital content interchanged through the Internet were utilized to solve a major concern in information and communication *** authors’difficulties were tampering detection,authentication,and integrity verification of the digital *** study develops an Automated Data Mining based Digital Text Document Watermarking for Tampering Attack Detection(ADMDTW-TAD)via the *** DM concept is exploited in the presented ADMDTW-TAD technique to identify the document’s appropriate characteristics to embed larger watermark *** presented secure watermarking scheme intends to transmit digital text documents over the Internet *** the watermark is embedded with no damage to the original document,it is then shared with the *** watermark extraction process is performed to get the original document *** experimental validation of the ADMDTW-TAD technique is carried out under varying levels of attack volumes,and the outcomes were inspected in terms of different *** simulation values indicated that the ADMDTW-TAD technique improved performance over other models.

关键词： Content authentication tampering attacks detection model security digital watermarking

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Validation of a Method for Characterization of Ethanol in Water by HS-GC-FID to Serve the Traceability of Halal Measurements

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Green and Sustainable Chemistry 2024年第2期14卷 17-28页

作者： Adel B. Shehata Abdulrahman R. Al Askar Mohammed A. Al Rasheed Abdulrahman M. Al Zahrany fahd A. Al Kharraa Sowailem A. Al Sowailem Chemistry Department/National Measurement and Calibration Center (NMCC) Saudi Standards Metrology and Quality Organization (SASO) Riyadh Kingdom of Saudi Arabia

The determination of the ethanol content in food products is of fundamental importance for HALAL certification. In this work, an analytical method for the determination of ethanol in water by headspace gas chromatography with flame ionization detector (HS-GC-FID) has been developed and validated for the use in characterization of ethanol reference materials. The validation study was carried out in the linear calibration range 100 - 1500 mg/kg using the NIST SRM 2900, nominal 95.6%. The studied performance characteristics of the method were the limit of detection, LOD, the limit of quantification LOQ, selectivity, linearity, precision, recovery and bias. The validation results showed that the method is selective, precise, accurate and free from any significant bias. The LOD and LOQ were 1.27 and 3.86 mg/kg respectively and the estimated expanded uncertainty was 2% indicating that the method is fit for the purpose of certification of ethanol in water reference materials.

关键词： Ethanol HS-GC-FID Validation Linearity Precision Bias

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Minimal Doubly Resolving Sets of Certain Families of Toeplitz Graph

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2681-2696页

作者： Muhammad Ahmad fahd Jarad Zohaib Zahid Imran Siddique Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Mathematics Cankaya UniversityEtimesgutAnkara06790Turkey Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402Taiwan

The doubly resolving sets are a natural tool to identify where diffusion occurs in a complicated *** realworld phenomena,such as rumour spreading on social networks,the spread of infectious diseases,and the spread of the virus on the internet,may be modelled using information diffusion in *** is obviously impractical to monitor every node due to cost and overhead limits because there are too many nodes in the network,some of which may be unable or unwilling to send information about their *** a result,the source localization problem is to find the number of nodes in the network that best explains the observed *** problem can be successfully solved by using its relationship with the well-studied related minimal doubly resolving set problem,which minimizes the number of observers required for accurate *** paper aims to investigate the minimal doubly resolving set for certain families of Toeplitz graph Tn(1,t),for t≥2 and n≥t+*** come to the conclusion that for Tn(1,2),the metric and double metric dimensions are equal and for Tn(1,4),the double metric dimension is exactly one more than the metric ***,the double metric dimension for Tn(1,3)is equal to the metric dimension for n=5,6,7 and one greater than the metric dimension for n≥8.

关键词： Family of Toeplitz graph resolving sets metric dimension doubly resolving sets double metric dimension

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On Nonlinear Conformable Fractional Order Dynamical System via Differential Transform Method

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1457-1472页

作者： Kamal Shah Thabet Abdeljawad fahd Jarad Qasem Al-Mdallal Department of Mathematics and Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Mathematics University of MalakandChakdara Dir(L)Khyber Pakhtunkhwa18000Pakistan Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematics Faculty of Arts and Sciences莂nkaya UniversityAnkara06790Turkey Department of Mathematical Sciences UAE UniversityAl-Ain15551United Arab Emirates

This article studies a nonlinear fractional order Lotka-Volterra prey-predator type dynamical *** the proposed study,we consider the model under the conformable fractional order derivative(CFOD).We investigate the mentioned dynamical system for the existence and uniqueness of at least one ***,Schauder and Banach fixed point theorems are utilized to prove our ***,an algorithm for the approximate analytical solution to the proposed problem has been *** this regard,the conformable fractional differential transform(CFDT)technique is used to compute the required results in the form of a *** Matlab-16,we simulate the series solution to illustrate our results ***,a comparison of our solution to that obtained for the Caputo fractional order derivative via the perturbation method is given.

关键词： Prey predator model existence results conformable fractional differential transform

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