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Optimal Machine Learning Enabled Intrusion Detection in Cyber-Physical System Environment

Computers, Materials & Continua 2022年第9期72卷 4691-4707页

作者： Bassam A.Y.Alqaralleh fahad Aldhaban Esam A.AlQarallehs Ahmad H.Al-Omari MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan Faculty of Science Computer Science DepartmentNorthern Border UniversityArar91431Saudi Arabia

Cyber-attacks on cyber-physical systems(CPSs)resulted to sensing and actuation misbehavior,severe damage to physical object,and safety *** learning(ML)models have been presented to hinder cyberattacks on the CPS environment;however,the non-existence of labelled data from new attacks makes their detection quite *** Detection System(IDS)is a commonly utilized to detect and classify the existence of intrusions in the CPS environment,which acts as an important part in secure CPS *** developments in deep learning(DL)and explainable artificial intelligence(XAI)stimulate new IDSs to manage cyberattacks with minimum complexity and high *** this aspect,this paper presents an XAI based IDS using feature selection with Dirichlet Variational Autoencoder(XAIIDS-FSDVAE)model for *** proposed model encompasses the design of coyote optimization algorithm(COA)based feature selection(FS)model is derived to select an optimal subset of ***,an intelligent Dirichlet Variational Autoencoder(DVAE)technique is employed for the anomaly detection process in the CPS ***,the parameter optimization of the DVAE takes place using a manta ray foraging optimization(MRFO)model to tune the parameter of the *** order to determine the enhanced intrusion detection efficiency of the XAIIDS-FSDVAE technique,a wide range of simulations take place using the benchmark *** experimental results reported the better performance of the XAIIDSFSDVAE technique over the recent methods in terms of several evaluation parameters.

关键词： Cyber-physical systems explainable artificial intelligence deep learning security intrusion detection metaheuristics

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Hybrid Metaheuristics Based License Plate Character Recognition in Smart City

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Computers, Materials & Continua 2022年第9期72卷 5727-5740页

作者： Esam A.Al.Qaralleh fahad Aldhaban Halah Nasseif Bassam A.Y.Alqaralleh Tamer AbuKhalil School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia Department of Computer Science Faculty of Information TechnologyAl-Hussein Bin Talal UniversityMa’an71111Jordan

Recent technological advancements have been used to improve the quality of living in smart *** the same time,automated detection of vehicles can be utilized to reduce crime rate and improve public *** the other hand,the automatic identification of vehicle license plate(LP)character becomes an essential process to recognize vehicles in real time scenarios,which can be achieved by the exploitation of optimal deep learning(DL)*** this article,a novel hybrid metaheuristic optimization based deep learning model for automated license plate character recognition(HMODL-ALPCR)technique has been presented for smart city *** major intention of the HMODL-ALPCR technique is to detect LPs and recognize the characters that exist in *** effective LP detection process,mask regional convolutional neural network(Mask-RCNN)model is applied and the Inception with Residual Network(ResNet)-v2 as the baseline *** addition,hybrid sunflower optimization with butterfly optimization algorithm(HSFO-BOA)is utilized for the hyperparameter tuning of the Inception-ResNetv2 ***,Tesseract based character recognition model is applied to effectively recognize the characters present in the *** experimental result analysis of the HMODL-ALPCR technique takes place against the benchmark dataset and the experimental outcomes pointed out the improved efficacy of the HMODL-ALPCR technique over the recent methods.

关键词： Smart city license plate recognition optimal deep learning metaheuristic algorithms parameter tuning

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Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

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Computers, Materials & Continua 2022年第2期70卷 2991-3004页

作者： Shibli Nisar Muhammad Asghar Khan fahad Algarni Abdul Wakeel M.Irfan Uddin Insaf Ullah Department of Electrical Engineering National University of Sciences and Technology(NUST)Islamabad44000Pakistan Hamdard Institute of Engineering&Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

One of the most commonly reported disabilities is vision loss,which can be diagnosed by an ophthalmologist in order to determine the visual system of a *** procedure,however,usually requires an appointment with an ophthalmologist,which is both time-consuming and expensive *** issues that can arise include a lack of appropriate equipment and trained practitioners,especially in rural *** on a cognitively motivated attribute extraction and speech recognition approach,this paper proposes a novel idea that immediately determines the eyesight *** proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for feature *** adaptive filter bank implementation is inspired by the principle of spectrum sensing in cognitive radio that is aware of its environment and adapts to statistical variations in the input stimuli by learning from the *** performance evaluation demonstrates the potential of our automated visual acuity test method to achieve comparable results to the clinical ground truth,established by the expert ophthalmologist’s *** overall accuracy achieved by the proposed model when compared with the expert ophthalmologist test is 91.875%.The proposed method potentially offers a second opinion to ophthalmologists,and serves as a cost-effective pre-screening test to predict eyesight loss at an early stage.

关键词： Eyesight test speech recognition HMM SVM feature extraction

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Hybrid Smart Contracts for Securing IoMT Data

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Computer Systems Science & Engineering 2023年第1期44卷 457-469页

作者： D.Palanikkumar Adel fahad alrasheedi P.Parthasarathi S.S.Askar Mohamed Abouhawwash Department of Computer Science and Engineering Dr NGP Institute of TechnologyCoimbatore641048India Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia Department of Computer Science and Engineering Bannari Amman Institute of TechnologySathy638401India Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Data management becomes essential component of patient *** of Medical Things(IoMT)performs a wireless communication between E-medical applications and human *** of consulting a doctor in the hospital,patients get health related information remotely from the *** main issues in the E-Medical application are lack of safety,security and priv-acy preservation of patient’s health care *** overcome these issues,this work proposes block chain based IoMT Processed with Hybrid consensus protocol for secured *** health data is collected from physician,smart devices *** main goal is to store this highly valuable health related data in a secure,safety,easy access and less cost-effective *** this research we combine two smart contracts such as Practical Byzantine Fault Tolerance with proof of work(PBFT-PoW).The implementation is done using cloud technology setup with smart contracts(PBFT-PoW).The accuracy rate of PBFT is 90.15%,for PoW is 92.75%and our proposed work PBFT-PoW is 99.88%.

关键词： PoW byzantine fault tolerance IoMT cloud computing health care data

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Review of heart transplantation from hepatitis C-positive donors

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World Journal of Transplantation 2022年第12期12卷 394-404页

作者： Palak Patel Nirav Patel fahad Ahmed Jason Gluck Department of Cardiology West Roxbury VA CenterWest RoxburyMA 02132United States Department of Cardiology University of ConnecticutHarford HospitalHartfordCT 06102United States Department of Cardiology University of CaliforniaCA 90065United States Department of Internal Medicine Hartford HospitalHartfordCT 06106United States Advanced Heart Failure Hartford HospitalHartfordCT 06102United States

Significant scarcity of a donor pool exists for heart transplantation(HT)as the prevalence of patients with end-stage refractory heart failure is increasing *** the discovery of effective direct-acting antiviral and favorable short-term outcomes following HT,the hearts from hepatitis C virus(HCV)patient are being utilized to increase the donor ***-term outcomes with regards to graft function,coronary artery vasculopathy,and kidney and liver disease is comparable in HCV-negative recipients undergoing HT from HCVpositive donors compared to HCV-negative donors.A significant high incidence of donor-derived HCV transmission was observed with great success of achieving sustained viral response with the use of direct-acting *** accepting HCV-positive organs,the donor pool has expanded with younger donors,a shorter waitlist time,and a reduction in waitlist ***,the longterm outcomes and impact of specific HCV genotypes remains to be *** reviewed the current literature on HT from HCV-positive donors.

关键词： Heart transplant Hepatitis C-positive donors Direct-acting antiviral Coronary allograft vasculopathy Allograft rejection

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Optimal Resource Allocation for NOMA Wireless Networks

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Computers, Materials & Continua 2023年第2期74卷 3249-3261页

作者： fahad R.Albogamy M.A.Aiyashi Fazirul Hisyam Hashim Imran Khan Bong Jun Choi Turabah University College Computer Sciences ProgramTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Jazan UniversityJazanP.O.Box 218Saudi Arabia Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra Malaysia(UPM)43400SerdangMalaysia Department of Electrical Engineering University of Engineering and Technology PeshawarP.O.Box 814Pakistan School of Computer Science and Engineering Soongsil UniversitySeoulKorea

The non-orthogonal multiple access(NOMA)method is a novel multiple access technique that aims to increase spectral efficiency(SE)and accommodate enormous user ***-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC),are performed at the receiving end to demodulate the necessary user *** its basic signal waveform,like LTE baseline,could be based on orthogonal frequency division multiple access(OFDMA)or discrete Fourier transform(DFT)-spread OFDM,NOMA superimposes numerous users in the power *** contrast to the orthogonal transmission method,the nonorthogonal method can achieve higher spectrum ***,it will increase the complexity of its *** power allocation techniques will have a direct impact on the system’s *** a result,in order to boost the system capacity,an efficient power allocation mechanism must be *** research developed an efficient technique based on conjugate gradient to solve the problem of downlink power *** major goal is to maximize the users’maximum weighted sum *** suggested algorithm’s most notable feature is that it converges to the global optimal *** compared to existing methods,simulation results reveal that the suggested technique has a better power allocation capability.

关键词： Non-orthogonalmultiple access wireless networks power domain 5G networks

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An Efficient Proxy Blind Signcryption Scheme for IoT

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Computers, Materials & Continua 2022年第3期70卷 4293-4306页

作者： Aamer Khan Insaf Ullah fahad Algarni Muhammad Naeem M.Irfan Uddin Muhammad Asghar Khan Department of Information Technology Abbottabad University of Science and TechnologyAbbotabadPakistan Hamdard Institute of Engineering and Technology Islamabad44000Pakistan College of Computing and Information Technology University of BishaBishaSaudi Arabia Institute of Computing Kohat University of Science and TechnologyKohatPakistan

Recent years have witnessed growing scientific research interest in the Internet of Things(IoT)technologies,which supports the development of a variety of applications such as health care,Industry 4.0,agriculture,ecological data management,and other various *** utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital ***,due to the wide-open nature of the Internet,it is important to ensure the anonymity,untraceably,confidentiality,and unforgeability of communication with efficient computational complexity and low *** designed a light weight and secure proxy blind signcryption for multi-digital messages based on a hyperelliptic curve(HEC).Our results outperform the available schemes in terms of computational cost and communication *** designed scheme also has the desired authentication,unforgeability of warrants and/or plaintext,confidentiality,integrity,and blindness,***,our scheme is more suitable for devices with low computation power such as mobiles and tablets.

关键词： Proxy signcryption multi-digital-documents proxy blind signcryption hyperelliptic curve IoT

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How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges

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Machine Intelligence Research 2023年第5期20卷 605-613页

作者： Haotong Qin Ge-Peng Ji Salman Khan Deng-Ping Fan fahad Shahbaz Khan Luc Van Gool Computer Vision Lab(CVL) ETH ZurichZurich 8001Switzerland College of Engineering Computing&CyberneticsAustralian National UniversityCanberra 8105Australia Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi 999041UAE

Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational ***,Bard has recently been updated to handle visual inputs alongside text prompts during *** Bard's impressive track record in handling textual inputs,we explore its capabilities in understanding and interpreting visual data(images)conditioned by text *** exploration holds the potential to unveil new insights and challenges for Bard and other forthcoming multi-modal Generative models,especially in addressing complex computer vision problems that demand accurate visual and language ***,in this study,we focus on 15 diverse task scenarios encompassing regular,camouflaged,medical,under-water and remote sensing data to comprehensively evaluate Bard's *** primary finding indicates that Bard still struggles in these vision scenarios,highlighting the significant gap in vision-based understanding that needs to be bridged in future *** expect that this empirical study will prove valuable in advancing future models,leading to enhanced capabilities in comprehending and interpreting finegrained visual *** project is released on https://***/htqin/GoogleBard-VisUnderstand.

关键词： Google Bard multi-modal understanding visual comprehension large language models conversational AI chatbot.

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Smart shale gas production performance analysis using machine learning applications

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Petroleum Research 2022年第1期7卷 21-31页

作者： fahad I.Syed Salem Alnaqbi Temoor Muther Amirmasoud K.Dahaghi Shahin Negahban The University of Kansas School of EngineeringChemical and Petroleum Engineering1450 Jayhawk Blvd.LawrenceKS66045USA

With the advancement of technology and innovation in the oil and gas industry,the production of liquid and gaseous hydrocarbon from conventional and unconventional resources has seen exponential ***,the USA and other oil giants have shifted their paradigm from conventional to unconventional resources of exploration and production of ***,there is still a perpetual force that exists to develop and devise new innovative approaches and methodologies for the exploration,extraction efficiencies,and production performance of *** better evaluate the impact of well attributes,reservoir characteristics and production behavior of well machine learning and artificial intelligence-based models have been developed by researchers that with the help of simulation and modeling provide us the true picture of reservoir performance without exploring and investing billions of *** review paper encompasses the literature published in the recent years and narrated the recent development made by researchers especially in the field of production performance estimation of shale gas by developing machine learning-based *** specifically,this paper deals with the major shale gas reservoir of North America including Marcellus shale,Eagle Ford shale,and Bakken ***,equations,input parameters,and formations that are considered key parameters for the development of the smart shale gas models are also discussed in this *** addition,the methodology comparison of different machine learning algorithms including their limitations and advantages are also presented.

关键词： Shale gas AI ML RTA DCA RF

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Rice Leaves Disease Diagnose Empowered with Transfer Learning

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Computer Systems Science & Engineering 2022年第9期42卷 1001-1014页

作者： Nouh Sabri Elmitwally Maria Tariq Muhammad Adnan Khan Munir Ahmad Sagheer Abbas fahad Mazaed Alotaibi College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

In the agricultural industry,rice infections have resulted in significant productivity and economic *** infections must be recognized early on to regulate and mitigate the effects of the *** diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses,reduce pesticide use,and boost ta country’s *** the health of a rice plant through its leaves is usually done as a manual ocular *** this manuscript,three rice plant diseases:Bacterial leaf blight,Brown spot,and Leaf smut,were identified using the Alexnet *** research shows that any reduction in rice plants will have a significant beneficial impact on alleviating global food hunger by increasing supply,lowering prices,and reducing production's environmental impact that affects the economy of any *** would be able to get more exact and faster results with this technology,allowing them to administer the most acceptable treatment *** Using Alex Net,the proposed approach achieved a 99.0%accuracy rate for diagnosing rice leaves disease.

关键词： Rice bacterial leaf blight brown spot leaf smut machine learning alexnet

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