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Continuous Mobile User Authentication Using a Hybrid CNN-Bi-LSTM Approach

计算机、材料和连续体（英文） 2023年第4期75卷 651-667页

作者： Sarah Alzahrani Joud Alderaan Dalya Alatawi Bandar alotaibi Department of Information Technology University of TabukTabuk71491Saudi Arabia Sensor Networks and Cellular Systems Research Center University of TabukTabuk71491Saudi Arabia

Internet of Things (IoT) devices incorporate a large amount ofdata in several fields, including those of medicine, business, and *** authentication is paramount in the IoT era to assure connecteddevices’ security. However, traditional authentication methods and conventionalbiometrics-based authentication approaches such as face recognition,fingerprints, and password are vulnerable to various attacks, including smudgeattacks, heat attacks, and shoulder surfing attacks. Behavioral biometrics isintroduced by the powerful sensing capabilities of IoT devices such as smartwearables and smartphones, enabling continuous authentication. ArtificialIntelligence (AI)-based approaches introduce a bright future in refining largeamounts of homogeneous biometric data to provide innovative user authenticationsolutions. This paper presents a new continuous passive authenticationapproach capable of learning the signatures of IoT users utilizing smartphonesensors such as a gyroscope, magnetometer, and accelerometer to recognizeusers by their physical activities. This approach integrates the convolutionalneural network (CNN) and recurrent neural network (RNN) models to learnsignatures of human activities from different users. A series of experiments areconducted using the MotionSense dataset to validate the effectiveness of theproposed method. Our technique offers a competitive verification accuracyequal to 98.4%.We compared the proposed method with several conventionalmachine learning and CNN models and found that our proposed modelachieves higher identification accuracy than the recently developed verificationsystems. The high accuracy achieved by the proposed method proves itseffectiveness in recognizing IoT users passively through their physical activitypatterns.

关键词： Human activity recognition recurrent neural network(RNN) internet of things(IoT) machine learning(ML)

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Leveraging Gradient-Based Optimizer and Deep Learning for Automated Soil Classification Model

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Computers, Materials & Continua 2023年第7期76卷 975-992页

作者： Hadeel Alsolai Mohammed Rizwanullah mashael Maashi Mahmoud Othman Amani A.Alneil Amgad Atta Abdelmageed Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityP.O.box 103786Riyadh11543Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Soil classification is one of the emanating topics and major concerns in many *** the population has been increasing at a rapid pace,the demand for food also increases *** approaches used by agriculturalists are inadequate to satisfy the rising demand,and thus they have hindered soil *** comes a demand for computer-related soil classification methods to support *** study introduces a Gradient-Based Optimizer and Deep Learning(DL)for Automated Soil Clas-sification(GBODL-ASC)*** presented GBODL-ASC technique identifies various kinds of soil using DL and computer vision *** the presented GBODL-ASC technique,three major processes are *** the initial stage,the presented GBODL-ASC technique applies the GBO algorithm with the EfficientNet prototype to generate feature *** soil categorization,the GBODL-ASC procedure uses an arithmetic optimization algorithm(AOA)with a Back Propagation Neural Network(BPNN)*** design of GBO and AOA algorithms assist in the proper selection of parameter values for the EfficientNet and BPNN models,*** demonstrate the significant soil classification outcomes of the GBODL-ASC methodology,a wide-ranging simulation analysis is performed on a soil dataset comprising 156 images and five *** simulation values show the betterment of the GBODL-ASC model through other models with maximum precision of 95.64%.

关键词： Soil classification earth sciences machine learning parameter optimization metaheuristics

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EACR-LEACH:Energy-Aware Cluster-based Routing Protocol for WSN Based IoT

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Computers, Materials & Continua 2022年第8期72卷 2159-2174页

作者： Sankar Sennan Kirubasri Youseef alotaibi Digvijay Pandey Saleh Alghamdi Department of Computer Science and Engineering Sona College of TechnologySalem636005India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Technical Education Department of Electronics EngineeringInstitute of Engineering and TechnologyDr.A.P.J.Abdul Kalam Technical UniversityLucknowIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Internet of Things(IoT)is a recent paradigm to improve human ***,number devices are connected to the Internet ***,the people can control and monitor the physical things in real-time without *** IoT plays a vital role in all kind of fields in our world such as agriculture,livestock,transport,and healthcare,grid system,connected home,elderly people carrying system,cypher physical system,retail,and intelligent *** IoT energy conservation is a challenging task,as the devices are made up of low-cost and low-power sensing devices and local *** networks have significant challenges in two areas:network lifespan and energy ***,the clustering is a right choice to prolong the energy in the *** LEACH clustering protocol,sometimes the same node acts as CH again and again *** overcome these issues,this paper proposes the Energy-Aware Cluster-based Routing(EACRLEACH)protocol in WSN based *** Cluster Head(CH)selection is a crucial task in clustering protocol inWSN based *** EACR-LEACH,the CH is selected by using the routing metrics,Residual Energy(RER),Number of Neighbors(NoN),Distance between Sensor Node and Sink(Distance)and Number of Time Node Act as CH(NTNACH).An extensive simulation is conducted on MATLAB *** accomplishment of EACR-LEACH is compared to LEACH and *** proposed EACR-LEACH protocol extends the network’s lifetime by 4%-8%and boosts throughput by 16%–24%.

关键词： Cluster head clustering protocol internet of things routing metrics wireless sensor networks

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Brain Tumor:Hybrid Feature Extraction Based on UNet and 3DCNN

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Computer Systems Science & Engineering 2023年第5期45卷 2093-2109页

作者： Sureshkumar Rajagopal Tamilvizhi Thanarajan Youseef alotaibi Saleh Alghamdi Center for System Design Chennai Institute of TechnologyChennai600069India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Automated segmentation of brain tumors using Magnetic Resonance Imaging(MRI)data is critical in the analysis and monitoring of disease *** a result,gliomas are aggressive and diverse tumors that may be split into intra-tumoral groups by using effective and accurate segmentation *** is intended to extract characteristics from an image using the Gray Level Co-occurrence(GLC)matrix feature extraction method described in the proposed *** Convolutional Neural Networks(CNNs),which are commonly used in biomedical image segmentation,CNNs have significantly improved the precision of the state-of-the-art segmentation of a brain *** two segmentation networks,a U-Net and a 3D CNN,we present a major yet easy combinative technique that results in improved and more precise *** U-Net and 3D CNN are used together in this study to get better and more accurate estimates of what is going *** the dataset,two models were developed and assessed to provide segmentation maps that differed fundamentally in terms of the segmented tumour ***,the estimates was made by two separate models that were put together to produce the final *** comparison to current state-of-the-art designs,the precision(percentage)was 98.35,98.5,and 99.4 on the validation set for tumor core,enhanced tumor,and whole tumor,respectively.

关键词： Medical imaging segmentation U-net 3D CNN brain tumor

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Enhancement of UAV Data Security and Privacy via Ethereum Blockchain Technology

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Computers, Materials & Continua 2023年第8期76卷 1797-1815页

作者： Sur Singh Rawat Youseef alotaibi Nitima Malsa Vimal Gupta Department of Computer Science and Engineering JSS Academy of Technical EducationNoida201301India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Unmanned aerial vehicles(UAVs),or drones,have revolutionized a wide range of industries,including monitoring,agriculture,surveillance,and supply ***,their widespread use also poses significant challenges,such as public safety,privacy,and ***,targetingUAVs have become more frequent,which highlights the need for robust security *** technology,the foundation of cryptocurrencies has the potential to address these *** study suggests a platform that utilizes blockchain technology tomanage drone operations securely and *** incorporating blockchain technology,the proposed method aims to increase the security and privacy of drone *** suggested platform stores information on a public blockchain located on Ethereum and leverages the Ganache platform to ensure secure and private blockchain *** wallet for Ethbalance is necessary for BCT *** present research finding shows that the proposed approach’s efficiency and security features are superior to existing *** study contributes to the development of a secure and efficient system for managing drone operations that could have significant applications in various *** proposed platform’s security measures could mitigate privacy concerns,minimize cyber security risk,and enhance public safety,ultimately promoting the widespread adoption of *** results of the study demonstrate that the blockchain can ensure the fulfillment of core security needs such as authentication,privacy preservation,confidentiality,integrity,and access control.

关键词： Unmanned aerial vehicles(UAVs) blockchain data privacy network security smart contract Ethereum

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MayGAN:Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia Form Blood Smear Images

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Computer Systems Science & Engineering 2023年第8期46卷 2039-2058页

作者： Neenavath Veeraiah Youseef alotaibi Ahmad F.Subahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

Leukemia,often called blood cancer,is a disease that primarily affects white blood cells(WBCs),which harms a person’s tissues and *** condition may be fatal when if it is not diagnosed and recognized at an early *** physical technique and lab procedures for Leukaemia identification are considered *** is crucial to use a quick and unexpected way to identify different forms of *** screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require *** deep-learning(DL)model-based segmentation and categorization techniques have already been introduced,although they still have certain *** order to enhance feature extraction and classification in such a practical way,Mayfly optimization with Generative Adversarial Network(MayGAN)is introduced in this ***,Generative Adversarial System(GAS)is integrated with Principal Component Analysis(PCA)in the feature-extracted model to classify the type of blood cancer in the *** semantic technique and morphological procedures using geometric features are used to segment the cells that makeup *** lymphocytic Leukaemia(ALL),acute myelogenous Leukaemia(AML),chronic lymphocytic Leukaemia(CLL),chronic myelogenous Leukaemia(CML),and aberrant White Blood Cancers(WBCs)are all successfully classified by the proposed MayGAN *** proposed MayGAN identifies the abnormal activity in the WBC,considering the geometric *** with the state-of-the-art methods,the proposed MayGAN achieves 99.8%accuracy,98.5%precision,99.7%recall,97.4%F1-score,and 98.5%Dice similarity coefficient(DSC).

关键词： Leukemia blood smear images optimization classification neural networks

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Mental Illness Disorder Diagnosis Using Emotion Variation Detection from Continuous English Speech

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Computers, Materials & Continua 2021年第12期69卷 3217-3238页

作者： S.Lalitha Deepa Gupta Mohammed Zakariah Yousef Ajami alotaibi Department of Electronics&Communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluruIndia Department of Computer Science&Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluruIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversitySaudi Arabia

Automatic recognition of human emotions in a continuous dialog model remains challenging where a speaker’s utterance includes several sentences that may not always carry a single *** work with standalone speech emotion recognition(SER)systems proposed for continuous speech only has been *** the recent decade,various effective SER systems have been proposed for discrete speech,i.e.,short speech *** would be more helpful if these systems could also recognize emotions from continuous ***,if these systems are applied directly to test emotions from continuous speech,emotion recognition performance would not be similar to that achieved for discrete speech due to the mismatch between training data(from training speech)and testing data(from continuous speech).The problem may possibly be resolved if an existing SER system for discrete speech is ***,in this work the author’s existing effective SER system for multilingual and mixed-lingual discrete speech is enhanced by enriching the cepstral speech feature set with bi-spectral speech features and a unique functional set of Mel frequency cepstral coefficient features derived from a sine filter *** augmentation is applied to combat skewness of the SER system toward certain *** using random forest is *** enhanced SER system is used to predict emotions from continuous speech with a uniform segmentation *** to data scarcity,several audio samples of discrete speech from the SAVEE database that has recordings in a universal language,i.e.,English,are concatenated resulting in multi-emotional speech ***,fear,sad,and neutral emotions,which are vital during the initial investigation of mentally disordered individuals,are selected to build six categories of multi-emotional *** results demonstrate the suitability of the proposed method for recognizing emotions from continuous speech as well as from discrete speech.

关键词： Continuous speech cepstral bi-spectral multi-emotional discrete emotion filter bank mental illness

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A Novel Gradient Boosted Energy Optimization Model(GBEOM)for MANET

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Computer Systems Science & Engineering 2023年第7期46卷 637-657页

作者： Neenavath Veeraiah Youseef alotaibi Saleh Alghamdi Satish Thatavarti Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P521180India Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramA.P522502India

Mobile Ad Hoc Network(MANET)is an infrastructure-less network that is comprised of a set of nodes that move *** MANET,the overall performance is improved through multipath multicast routing to achieve the quality of service(quality of service).In this,different nodes are involved in the information data collection and transmission to the destination nodes in the *** different nodes are combined and presented to achieve energy-efficient data transmission and classification of the *** route identification and routing are established based on the data broadcast by the network *** transmitting the data packet,evaluating the data delivery ratio is necessary to achieve optimal data transmission in the ***,energy consumption and overhead are considered essential factors for the effective data transmission rate and better data delivery *** this paper,a Gradient-Based Energy Optimization model(GBEOM)for the route in MANET is proposed to achieve an improved data delivery ***,the Weighted Multi-objective Cluster-based Spider Monkey Load Balancing(WMC-SMLB)technique is utilized for obtaining energy efficiency and load balancing *** WMC algorithm is applied to perform an efficient node clustering process from the considered mobile nodes in *** balancing efficiency is improved with a higher data delivery ratio and minimum routing overhead based on the residual energy and bandwidth ***,the Gradient Boosted Multinomial ID3 Classification algorithm is applied to improve the performance of multipath multicast routing in MANET with minimal energy consumption and higher load balancing *** proposed GBEOM exhibits∼4%improved performance in MANET routing.

关键词： Manet routing load balancing clustering gradient boosting

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Reliability Analysis of HEE Parameters via Progressive Type-II Censoring with Applications

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2761-2793页

作者： Heba S.Mohammed Mazen Nassar Refah alotaibi Ahmed Elshahhat Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Statistics Faculty of CommerceZagazig UniversityZagazigEgypt Faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A new extended exponential lifetime model called Harris extended-exponential(HEE)distribution for data modelling with increasing and decreasing hazard rate shapes has been *** the reliability context,researchers prefer to use censoring plans to collect data in order to achieve a compromise between total test time and/or test sample ***,this study considers both maximum likelihood and Bayesian estimates of the Harris extended-exponential distribution parameters and some of its reliability indices using a progressive Type-II censoring *** the premise of independent gamma priors,the Bayesian estimation is created using the squared-error and general entropy loss *** to the challenging form of the joint posterior distribution,to evaluate the Bayes estimates,samples from the full conditional distributions are generated using Markov Chain Monte Carlo *** each unknown parameter,the highest posterior density credible intervals and asymptotic confidence intervals are also *** a simulated study,the usefulness of the various suggested strategies is *** optimal progressive censoring plans are also shown,and various optimality criteria are *** actual data sets,taken from engineering and veterinary medicine areas,are analyzed to show how the offered point and interval estimators can be used in practice and to verify that the proposed model furnishes a good fit than other lifetimemodels:alpha power exponential,generalized-exponential,Nadarajah-Haghighi,Weibull,Lomax,gamma and exponential *** evaluations revealed that in the presence of progressively Type-II censored data,the Bayes estimation method against the squared-error(symmetric)loss is advised for getting the point and interval estimates of the HEE distribution.

关键词： Harris extended-exponential model progressive Type-II censoring reliability maximum likelihood MCMC techniques Monte Carlo experiments

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CO oxidation and 4-nitrophenol reduction over ceria-promoted platinum nanoparticles impregnated with ZSM-5 zeolite

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Journal of Rare Earths 2022年第8期40卷 1247-1254页

作者： Zeinhom M.El-Bahy Mohammed T.alotaibi Salah M.El-Bahy Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt Department of Chemistry Turabah University CollegeTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

Active new ceria-promoted platinum supported on ZSM-5 catalysts were prepared and characterized by X-ray diffraction(XRD),Fourier transform infrared spectra(FTIR),transform electron microscopy(TEM),temperature programmed desorption(TPD),and FTIR of CO *** samples were prepared by the incipient wetness impregnation method and calcined at 500℃.The XRD patterns and FTIR spectra prove that the zeolite framework is kept unaltered after metal *** images prove the presence of Pt nanoparticles with particle size starting from 14 to 27 *** FTIR data suggest the formation of Pt-O-Ce ***-situ FTIR of CO adsorption over reduced samples proves the presence of Pt~0 only,and no Pt^(n+)-CO species are *** prepared catalysts were tested in both oxidation reaction(CO oxidation) in the gas phase and in reduction reaction(4-nitrophenol reduction) in the aqueous ***,CO oxidation by O_(2) results in the formation of a CO_(2) peak at 2347 cm^(-1) as the only CO oxidation product in the studied frequency *** intensity of the CO_(2) peak increases after the addition of Ce,and it is 4 times higher in Pt_(1) Ce_(0.5)ZSM-5 than that in the Ce-free *** to the FTIR data and previous reports,the increase in the catalytic activity may be due to the formation of Pt-O-Ce ***,Ce-promoted Pt_(1) ZSM5 also exhibits enhanced catalytic activity towards the reduction of 4-nitrophenol to 4-aminophenol by NaBH_(4) in the aqueous *** first-order rate constant of the reduction increases ≈13 times after incorporating equal ratios of Pt and Ce(Pt_(1) Ce_(1)ZSM-5),and the activation energy(E_(a)) decreases to 40% of that in the reaction over Pt_(1) ZSM-5.

关键词： 4-Nitrophenol CO oxidation TPD-CO Platinum-cerium ZSM-5 Rare earths

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