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International Journal of Biomathematics 2024年第5期17卷 229-256页

作者： Hiba El Asraoui M'hamed El Omari Ali El Mfadel khalid hilal Laboratory of Applied Mathematics Scientific Computing Sultan Moulay Slimane University BP 523 Beni MellalMorocco

In this paper,we investigate the existence of solutions and analyze the large-time behavior for Gurtin-Maccamy population model involving conformable fractional *** a preliminary step,we construct a generic structure of the solution associated with our proposed model by utilizing some basic properties and tools of conformable fractional *** establish the existence of a unique solution of the given model with the given initial *** last,by using the upper and lower solutions for the characteristic equation,we define the upper and lower boundaries for the obtained solution and describe the large-time behavior of the total population.

关键词： Age-dependent population conformable fractional operator upper and lower boundary of the solution dynamics of populations

Experimental Behavior of Partially Prestressed High Strength Concrete Beams

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Open Journal of Civil Engineering 2013年第3期3卷 26-32页

作者： Shady H. Salem khalid M. hilal Tarek K. Hassan Ahmed S. Essawy Department of Structural Engineering Faculty of Engineering Ain Shams University Cairo Egypt

In the last few decades, prestressed concrete has been rapidly used in bridge engineering due to the enormous development in the construction techniques and the increasing need for long span bridges. High strength concrete has been also more widely spread than the past. It currently becomes more desirable as it has better mechanical properties and durability performance. Major defect of fully prestressed concrete is its low ductility;it may produce less alarming signs than ordinary reinforced concrete via smaller deflection and limited cracking. Therefore, partially prestressing is considered an intermediate design between the two extremes. So, combining high strength concrete with partial prestressing will result in a considerable development in the use of prestressed concrete structures regarding the economical and durability view points. This study presents the results of seven partially prestressed high strength concrete beams in flexure. The tested beams are used to investigate the influence of concrete compressive strength, prestressing steel ratio and flange width on the behavior of partially prestressed beams. The experimentally observed behaviors of all beams were presented in terms of the cracking load, ultimate load, deflection, cracking behavior and failure modes.

关键词： Partially Prestressed High Strength Concrete Beams Serviceability Behavior Failure Modes

A Cubic Spline Method for Solving a Unilateral Obstacle Problem

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American Journal of Computational Mathematics 2012年第3期2卷 217-222页

作者： El Bekkey Mermri Abdelhafid Serghini Abdelmajid El hajaji khalid hilal Department of Mathematics and Computer Science Faculty of Science University Mohammed Premier Oujda Morocco Department of Mathematics Faculty of Science and Technology University Sultan Moulay Slimane Beni-Mellal Morocco Department of Mathematics Faculty of Science and TechnologyUniversity Sultan Moulay Slimane Beni-Mellal Morocco MATSI Laboratory ESTO University Mohammed Premier Oujda Morocco

This paper, we develop a numerical method for solving a unilateral obstacle problem by using the cubic spline collocation method and the generalized Newton method. This method converges quadratically if a relation-ship between the penalty parameter and the discretization parameter h is satisfied. An error estimate between the penalty solution and the discret penalty solution is provided. To validate the theoretical results, some numerical tests on one dimensional obstacle problem are presented.

关键词： Obstacle Problem Spline Collocation Nonsmooth Equation Generalized Newton Method

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 *** experimental 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

Interobserver reliability between pediatric radiologists and residents in ultrasound evaluation of intraventricular hemorrhage in premature infants

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World Journal of Radiology 2022年第11期14卷 367-374页

作者： Muhammad Danish Barakzai Ayimen khalid Zara Za Sheer Faheemullah Khan Naila Nadeem Noman Khan Kiran hilal Department of Radiology The Hospital for Sick ChildrenToronto 555Canada Department of Radiology Aga Khan University HospitalKarachi 74800Pakistan Community Health Sciences Aga Khan University HospitalKarachi 74800Pakistan

BACKGROUND Germinal matrix intraventricular hemorrhage(IVH)may contribute to significant morbidity and mortality in premature *** identification and grading of IVH affect decision-making and clinical *** is possibility of misinterpretation of the ultrasound appearances,and the interobserver variability has not been investigated between radiology resident and board-certified *** To assess interobserver reliability between senior radiology residents performing bedside cranial ultrasound during on-call hours and pediatric *** From June 2018 to June 2020,neonatal cranial ultrasound examinations were performed in neonatal intensive care *** findings were recorded by the residents performing the ultrasound and the pediatric attending *** In total,200 neonates were included in the study,with a mean gestational age of 30.9 *** agreement for higher grade(Grade III&IV)IVH was *** was substantial agreement for lower grade(Grade I&II)*** There is strong agreement between radiology residents and pediatric radiologists,which is higher for high grade IVHs.

关键词： Ultrasound head Neonatal cranial ultrasound Cranial ultrasound Intraventricular hemorrhage Neonatal intraventricular hemorrhage

Sign Language Recognition and Classification Model to Enhance Quality of Disabled People

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Computers, Materials & Continua 2022年第11期73卷 3419-3432页

作者： Fadwa Alrowais Saud S.Alotaibi Sami Dhahbi Radwa Marzouk Abdullah Mohamed Anwer Mustafa hilal Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia University of Tunis EL Manar Higher Institute of ComputerResearch Team on Intelligent Systems in Imaging and Artificial Vision(Siiva)–Lab LimticAryanah2036Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Research Centre Future University in EgyptNew Cairo11745Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

Sign language recognition can be considered as an effective solution for disabled people to communicate with *** helps them in conveying the intended information using sign languages without any *** advancements in computer vision and image processing techniques can be leveraged to detect and classify the signs used by disabled people in an effective *** optimization algorithms can be designed in a manner such that it fine tunes the hyper parameters,used in Deep Learning(DL)models as the latter considerably impacts the classification *** this motivation,the current study designs the Optimal Deep Transfer Learning Driven Sign Language Recognition and Classification(ODTL-SLRC)model for disabled *** aim of the proposed ODTL-SLRC technique is to recognize and classify sign languages used by disabled *** proposed ODTL-SLRC technique derives EfficientNet model to generate a collection of useful feature *** addition,the hyper parameters involved in EfficientNet model are fine-tuned with the help of HGSO ***,Bidirectional Long Short Term Memory(BiLSTM)technique is employed for sign language *** proposed ODTL-SLRC technique was experimentally validated using benchmark dataset and the results were inspected under several *** comparative analysis results established the superior performance of the proposed ODTL-SLRC technique over recent approaches in terms of efficiency.

关键词： Sign language image processing computer vision disabled people deep learning parameter tuning

Automated Deep Learning Based Melanoma Detection and Classification Using Biomedical Dermoscopic Images

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Computers, Materials & Continua 2023年第2期74卷 2443-2459页

作者： Amani Abdulrahman Albraikan Nadhem NEMRI Mimouna Abdullah Alkhonaini Anwer Mustafa hilal Ishfaq Yaseen Abdelwahed Motwakel Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Melanoma remains a serious illness which is a common formof skin *** the earlier detection of melanoma reduces the mortality rate,it is essential to design reliable and automated disease diagnosis model using dermoscopic *** recent advances in deep learning(DL)models find useful to examine the medical image and make proper *** this study,an automated deep learning based melanoma detection and classification(ADL-MDC)model is *** goal of the ADL-MDC technique is to examine the dermoscopic images to determine the existence of *** ADL-MDC technique performs contrast enhancement and data augmentation at the initial ***,the k-means clustering technique is applied for the image segmentation *** addition,Adagrad optimizer based Capsule Network(CapsNet)model is derived for effective feature extraction ***,crow search optimization(CSO)algorithm with sparse autoencoder(SAE)model is utilized for the melanoma classification *** exploitation of the Adagrad and CSO algorithm helps to properly accomplish improved performance.A wide range of simulation analyses is carried out on benchmark datasets and the results are inspected under several *** simulation results reported the enhanced performance of the ADL-MDC technique over the recent approaches.

关键词： Biomedical images dermoscopic images deep learning melanoma detection machine learning

Quantum Artificial Intelligence Based Node Localization Technique for Wireless Networks

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Computers, Materials & Continua 2022年第10期73卷 327-342页

作者： Hanan Abdullah Mengash Radwa Marzouk Siwar Ben Haj Hassine Anwer Mustafa hilal Ishfaq Yaseen Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,*** the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor *** comprises a massive number of SNs and records the position of the nodes,which becomes a tedious ***,the SNs might be subjected to node mobility and the position alters with ***,a precise node localization(NL)manner is required for determining the location of the *** this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for *** goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor *** QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating *** addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown *** demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.

关键词： Artificial intelligence wireless communication wireless sensor networks metaheuristics quantum computing node localization

Deep Learning Empowered Cybersecurity Spam Bot Detection for Online Social Networks

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Computers, Materials & Continua 2022年第3期70卷 6257-6270页

作者： Mesfer Al Duhayyim Haya Mesfer Alshahrani Fahd NAl-Wesabi Mohammed Alamgeer Anwer Mustafa hilal Mohammed Rizwanullah 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 ITSana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Cybersecurity encompasses various elements such as strategies,policies,processes,and techniques to accomplish availability,confidentiality,and integrity of resource processing,network,software,and data from *** this scenario,the rising popularity of Online Social Networks(OSN)is under threat from spammers for which effective spam bot detection approaches should be *** studies have developed different approaches for the detection of spam bots in *** those techniques primarily concentrated on hand-crafted features to capture the features of malicious users while the application of Deep Learning(DL)models needs to be *** this motivation,the current research article proposes a Spam Bot Detection technique using Hybrid DL model abbreviated as *** proposed SBD-HDL technique focuses on the detection of spam bots that exist in *** technique has different stages of operations such as pre-processing,classification,and parameter ***,SBD-HDL technique hybridizes Graph Convolutional Network(GCN)with Recurrent Neural Network(RNN)model for spam bot classification *** order to enhance the detection performance of GCN-RNN model,hyperparameters are tuned using Lion Optimization Algorithm(LOA).Both hybridization of GCN-RNN and LOA-based hyperparameter tuning process make the current work,a first-of-its-kind in this *** experimental validation of the proposed SBD-HDL technique,conducted upon benchmark dataset,established the supremacy of the technique since it was validated under different measures.

关键词： Cybersecurity spam bot data classification social networks twitter deep learning