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Text Analysis-Based Watermarking Approach for Tampering Detection of English Text

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Computers, Materials & Continua 2021年第6期67卷 3701-3719页

作者： fahd n.al-wesabi Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen

Due to the rapid increase in the exchange of text information via internet networks,the security and the reliability of digital content have become a major research *** main challenges faced by researchers are authentication,integrity verication,and tampering detection of the digital *** this paper,text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text *** proposed approach embeds and detects the watermark logically without altering the original English text *** on hidden Markov model(HMM),the fourth level order of the word mechanism is used to analyze the contents of the given English text to nd the interrelationship between the *** extracted features are used as watermark information and integrated with digital zero-watermarking *** detect eventual tampering,the proposed approach has been implemented and validated with attacked English *** were performed using four standard datasets of varying lengths under multiple random locations of insertion,reorder,and deletion *** experimen.al and simulation results prove the tampering detection accuracy of our method against all kinds of tampering *** results show that our proposed approach outperforms all the other baseline approaches in terms of tampering detection accuracy.

关键词： Text analysis English language processing hidden Markov model zero-watermarking content authentication tampering detection

A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

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Computers, Materials & Continua 2021年第1期66卷 195-211页

作者： fahd n.al-wesabi Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen

In this paper,a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text *** proposed approach known as Second order of alphanumeric Mechanism of Markov model and Zero-Watermarking Approach(SAMMZWA).Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed *** SAMMZWA approach embeds and detects the watermark logically without altering the original text *** extracted features are used as a watermark information and integrated with digital zero-watermarking *** detect eventual tampering,SAMMZWA has been implemented and validated with attacked Arabic *** were performed on four datasets of varying lengths under multiple random locations of insertion,reorder and deletion *** experimen.al results show that our method is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

关键词： HMM nLP text analysis zero-watermarking tampering detection

An Optimized English Text Watermarking Method Based on natural Language Processing Techniques

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Computers, Materials & Continua 2021年第11期69卷 1519-1536页

作者： fahd n.al-wesabi Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen

In this paper,the text analysis-based approach RTADZWA(Reliable Text Analysis and Digital Zero-Watermarking Approach)has been proposed for transferring and receiving authentic English text via the *** level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on *** analysis and text zero-watermarking techniques have been integrated by RTADZWA approach to improving the performance,accuracy,capacity,and robustness issues of the previous literature proposed by the *** RTADZWA approach embeds and detects the watermark logically without altering the original text document to embed a *** has been implemented using PHP with VS code *** experimen.al and simulation results using standard datasets of varying lengths show that the proposed approach can obtain high robustness and better detection accuracy of tampering common random insertion,reorder,and deletion attacks,e.g.,Comparison results with baseline approaches also show the advantages of the proposed approach.

关键词： Text analysis nLP hidden markov model zero-watermarking content authentication tampering detection

A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

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Computers, Materials & Continua 2020年第11期65卷 1137-1156页

作者： fahd n.al-wesabi Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen

Text information is principally dependent on the natural ***,improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers *** authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the *** this paper,an intelligent text Zero-Watermarking approach SETZWMWMM(Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model)has been proposed for the content authentication and tampering detection of English text *** SETZWMWMM approach embeds and detects the watermark logically without altering the original English text *** on Hidden Markov Model(HMM),Third level order of word mechanism is used to analyze the interrelationship between contexts of given English *** extracted features are used as a watermark information and integrated with digital zero-watermarking *** detect eventual tampering,SETZWMWMM has been implemented and validated with attacked English *** were performed on four datasets of varying lengths under multiple random locations of insertion,reorder and deletion *** experimen.al results show that our method is more sensitive and efficient for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

关键词： Content authentication hidden Markov model zero-watermarking nLP tampering detection.

An Optimized algorithm for Resource allocation for D2D in Heterogeneous networks

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Computers, Materials & Continua 2022年第2期70卷 2923-2936页

作者： Abdul Kadir Hamid fahd n.al-wesabi nadhem nemri Ammar Zahary Imran Khan Department of Electrical&Computer Engineering University of SharjahSharjahUnited Arab Emirates Department of Computer Science King Khalid UniversityMuhayel AseerKSA Faculty of Computer and IT Sana’a UniversitySanaaYemen Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPaki

With the emergence of 5G mobile multimedia services,end users’demand for high-speed,low-latency mobile communication network access is *** them,the device-to-device(D2D)communication is one of the considerable *** D2D communication,the data does not need to be relayed and forwarded by the base station,but under the control of the base station,a direct local link is allowed between two adjacent mobile *** flexible communicationmode reduces the processing bottlenecks and coverage blind spots of the base station,and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless *** of the important factors which affects the quality-of-service(QoS)of D2D communications is co-channel *** order to solve this problem of co-channel interference,this paper proposes a graph coloring based *** main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user *** proposed algorithm also provides simpler power *** heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is *** results show that the proposed algorithm effectively reduced the co-channel interference,power consumption and improved the system throughput as compared with existing algorithms.

关键词： 5G device-to-device communication wireless networks spectrum

Hand Gesture Recognition for Disabled People Using Bayesian Optimization with Transfer Learning

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Intelligent Automation & Soft Computing 2023年第6期36卷 3325-3342页

作者： Fadwa alrowais Radwa Marzouk fahd n.al-wesabi Anwer Mustafa Hilal Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sign language recognition can be treated as one of the efficient solu-tions for disabled people to communicate with *** helps them to convey the required data by the use of sign language with no *** latest develop-ments in computer vision and image processing techniques can be accurately uti-lized for the sign recognition process by disabled *** Sign Language(ASL)detection was challenging because of the enhancing intraclass similarity and higher *** article develops a new Bayesian Optimiza-tion with Deep Learning-Driven Hand Gesture Recognition Based Sign Language Communication(BODL-HGRSLC)for Disabled *** BODL-HGRSLC technique aims to recognize the hand gestures for disabled people’s *** presented BODL-HGRSLC technique integrates the concepts of compu-ter vision(CV)and DL *** the presented BODL-HGRSLC technique,a deep convolutional neural network-based residual network(Resnet)model is applied for feature ***,the presented BODL-HGRSLC model uses Bayesian optimization for the hyperparameter tuning *** last,a bidir-ectional gated recurrent unit(BiGRU)model is exploited for the HGR procedure.A wide range of experiments was conducted to demonstrate the enhanced perfor-mance of the presented BODL-HGRSLC *** comprehensive comparison study reported the improvements of the BODL-HGRSLC model over other DL models with maximum accuracy of 99.75%.

关键词： Deep learning hand gesture recognition disabled people computer vision bayesian optimization

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

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Computer Systems Science & Engineering 2023年第8期46卷 1929-1945页

作者： Anwer Mustafa Hilal Fadwa alrowais fahd n.al-wesabi Radwa Marzouk Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Sciences 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 UniversityMahayilSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt

The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing(nLP)and computer vision(CV).It can be driven by applications like image retrieval or indexing,virtual assistants,image understanding,and support of visually impaired people(VIP).Though the VIP uses other senses,touch and hearing,for recognizing objects and events,the quality of life of those persons is lower than the standard *** Image captioning generates captions that will be read loudly to the VIP,thereby realizing matters happening around *** article introduces a Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System(RDOAI-ICS)for Visually Impaired *** presented RDOAI-ICS technique aids in generating image captions for *** presented RDOAIICS technique utilizes a neural architectural search network(nASnet)model to produce image ***,the RDOAI-ICS technique uses the radial basis function neural network(RBFnn)method to generate a textual *** enhance the performance of the RDOAI-ICS method,the parameter optimization process takes place using the RDO algorithm for nasnet and the butterfly optimization.algorithm(BOA)for the RBFnn model,showing the novelty of the *** experimen.al evaluation of the RDOAI-ICS method can be tested using a benchmark *** outcomes show the enhancements of the RDOAI-ICS method over other recent Image captioning approaches.

关键词： Machine learning image captioning visually impaired people parameter tuning artificial intelligence metaheuristics

Machine Learning Based Depression,Anxiety,and Stress Predictive Model During COVID-19 Crisis

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Computers, Materials & Continua 2022年第3期70卷 5803-5820页

作者： fahd n.al-wesabi Hadeel alsolai Anwer Mustafa Hilal Manar Ahmed Hamza Mesfer al Duhayyim noha negm Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Computer Science Department King Khaled UniversityKSA Faculty of Science Mathematics and Computer Science DepartmentMenoufia UniversityEgypt

Corona Virus Disease-2019(COVID-19)was reported at first in Wuhan city,China by December *** Health Organization(WHO)declared COVID-19 as a pandemic i.e.,global health crisis onMarch 11,*** outbreak of COVID-19 pandemic and subsequent lockdowns to curb the spread,not only affected the economic status of a number of countries,but it also resulted in increased levels of Depression,Anxiety,and Stress(DAS)among ***,there is a need exists to comprehend the relationship among psycho-social factors in a country that is hypothetically affected by high levels of stress and fear;with tremendously-limitingmeasures of social distancing and lockdown in force;and with high rates of new cases and *** this motivation,the current study aims at investigating theDAS levels among college students during COVID-19 lockdown since they are identified as a highly-susceptible *** current study proposes to develop Intelligent Feature Subset Selection withMachine Learning-based DAS predictive(IFSSML-DAS)*** presented IFSSML-DAS model involves data preprocessing,Feature Subset Selection(FSS),classification,and parameter ***,IFSSML-DAS model uses Group Gray Wolf Optimization based FSS(GGWO-FSS)technique to reduce the curse of *** addition,Beetle Swarm Optimization based Least Square Support Vector Machine(BSO-LSSVM)model is also employed for classification in which the weight and bias parameters of the LSSVM model are optimally adjusted using BSO *** performance of the proposed IFSSML-DAS model was tested using a benchmark DASS-21 dataset and the results were investigated under different *** outcome of the study suggests the development of specialized programs to handleDAS among population so as to overcome COVID-19 crisis.

关键词： Psycho-social factors covid-19 crisis management predictive models decision making machine learning

Securing Arabic Contents algorithm for Smart Detecting of Illegal Tampering Attacks

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Computers, Materials & Continua 2022年第2期70卷 2879-2894页

作者： Mesfer al Duhayyim Manal Abdullah alohali fahd n.al-wesabi Anwer Mustafa Hilal Mohammad Medani Manar Ahmed Hamza Department of natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Themost common digital media exchanged via the Internet is in text *** Arabic language is considered one of themost sensitive languages of content modification due to the presence of diacritics that can cause a change in the *** this paper,an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the *** core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking *** watermark key will be generated by utilizing the extracted features of the text analysis process using the third order and word level of the Markov *** Embedding and detection processes of the proposed scheme will be performed logically without the effect of the original *** proposed scheme is implemented using PHP with VS code *** simulation results,using varying sizes of standard datasets,show that the proposed scheme can obtain high reliability and provide better accuracy of the common illegal tampering *** results with other baseline techniques show the added value of the proposed scheme.

关键词： Tampering detection zero-watermarking soft computing text analysis hidden Markov model