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Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

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Computers, Materials & Continua 2024年第7期80卷 1277-1304页

作者： Shazielya Shamsul Mohammed A.H.Ali Salwa Hanim Abdul-Rashid Atef M.Ghaleb fahad M.Alqahtani Department of Mechanical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Centre for Sustainable and Smart Manufacturing(CSSM) Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Industrial Engineering College of EngineeringAlfaisal UniversityRiyadh11533Saudi Arabia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout *** is achieved by integrating a novel ai algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID *** enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout *** potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingMATLAB and ILSL ***,it was deployed in a small-scale environment to validate its real-world *** show that RFID with the proposed new algorithm ILSL and ai basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

关键词： Smart checkout system RFID technology improved laser simulator logic(ILSL) reduce noise checkout process

Artificial Intelligence Based Threat Detection in Industrial Internet of Things Environment

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Computers, Materials & Continua 2022年第12期73卷 5809-5824页

作者： fahad F.Alruwaili College of Computing and Information Technology Shaqra UniversitySharqaSaudi Arabia

Internet of Things(IoT)is one of the hottest research topics in recent years,thanks to its dynamic working mechanism that integrates physical and digital world into a single *** technology,applied in industries,is termed as Industrial IoT(IIoT).IIoT has been found to be highly susceptible to attacks from adversaries,based on the difficulties observed in IIoT and its increased dependency upon internet and communication *** or accidental attacks on these approaches result in catastrophic effects like power outage,denial of vital health services,disruption to civil service,etc.,Thus,there is a need exists to develop a vibrant and powerful for identification and mitigation of security vulnerabilities in *** this view,the current study develops an ai-based Threat Detection and Classification model for IIoT,abbreviated as aiTDC-IIoT *** presented aiTDC-IIoT model initially pre-processes the input data to transform it into a compatible *** addition,WhaleOptimizationAlgorithm based Feature Selection(WOA-FS)is used to elect the subset of ***,Cockroach Swarm Optimization(CSO)is employed with Random Vector Functional Link network(RVFL)technique for threat ***,CSO algorithm is applied to appropriately adjust the parameters related to RVFL *** performance of the proposed aiTDC-IIoT model was validated under benchmark *** experimental results established the supremacy of the proposed aiTDC-IIoT model over recent approaches.

关键词： Security industrial internet of things threat detection artificial intelligence feature selection

IoT & ai Enabled Three-Phase Secure and Non-Invasive COVID 19 Diagnosis System

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Computers, Materials & Continua 2022年第4期71卷 423-438页

作者： Anurag Jain Kusum Yadav Hadeel fahad Alharbi Shamik Tiwari Virtualization Department School of Computer ScienceUniversity of Petroleum and Energy StudiesDehradun248007UttarakhandIndia College of Computer Science and Engineering University of Ha’ilHa’ilKingdom of Saudi Arabia

Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December *** to the similarity in initial symptoms with viral fever,it is challenging to identify this virus ***-detection of this virus at the early stage results in the death of the *** and densely populated countries face a scarcity of resources like hospitals,ventilators,oxygen,and healthcare *** like the Internet of Things(IoT)and artificial intelligence can play a vital role in diagnosing the COVID-19 virus at an early *** minimize the spread of the pandemic,IoT-enabled devices can be used to collect patient’s data remotely in a secure *** data can be analyzed through a deep learning model to detect the presence of the COVID-19 *** this work,the authors have proposed a three-phase model to diagnose covid-19 by incorporating a chatbot,IoT,and deep learning *** phase one,an artificially assisted chatbot can guide an individual by asking about some common *** case of detection of even a single sign,the second phase of diagnosis can be considered,consisting of using a thermal scanner and pulse *** case of high temperature and low oxygen saturation levels,the third phase of diagnosis will be recommended,where chest radiography images can be analyzed through an ai-based model to diagnose the presence of the COVID-19 virus in the human *** proposed model reduces human intervention through chatbot-based initial screening,sensor-based IoT devices,and deep learning-based X-ray *** also helps in reducing the mortality rate by detecting the presence of the COVID-19 virus at an early stage.

关键词： COVID-19 internet of things deep learning chatbot X-ray capsule network convolutional neural network

Pharmacokinetic interaction of Acacia catechu with CYP1A substrate theophylline in rabbits

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Journal of Traditional Chinese Medicine 2015年第5期35卷 588-593页

作者： Abdullah Mohammed ai-Mohizea Mohammad Raish Abdul Ahad fahad Ibrahim ai-Jenoobi Mohd Aftab Alam Department of Pharmaceutics College of PharmacyKing Saud University

OBJECTIVE:To investigate the effect of black catechu(BC) on the pharmacokinetics of theophylline(CYP1A2 substrate,with narrow therapeutic index)in ***:In the present investigation the effect of BC on the pharmacokinetics of theophylline,a CYP1A2 substrate was *** the study,BC(264 mg/kg,p.o.) or saline(control group) was given to rabbits for 7 consecutive days and on the 8^(th)day theophylline(16 mg/kg) was administered orally one hour after BC or saline *** samples were withdrawn at different time intervals(0.5,1,1.5,2,3,4,6,8,12,24 and 36 h) from the marginal ear ***:The pretreatment of rabbits with BC resulted in a significant increase in maximum blood concentration,time of peak concentration and area under the concentration time profile curve until last observation which was about 41.32%,35.71%and 15.03%,*** decreases in clearance,volume of distribution,and half-life were *** is suggested that BC pretreatment decreases the CYP1 A metabolic activity leading to increase in bioavailability and decrease in oral clearance of theophylline,which may be due to inhibition of CYP1 ***:BC can significantly alter theophylline pharmacokinetics in vivo possibly due to inhibition of CYP1 A and P-glycoprotein *** on these results,precaution should be exercised when administering BC with CYP1 A substrate.

关键词：药代动力学茶碱家兔相互作用底物 CYP1A2 血药浓度生理盐水

Application of ML&ai to model petrophysical and geomechanical properties of shale reservoirs e A systematic literature review

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Petroleum 2022年第2期8卷 158-166页

作者： fahad I.Syed Abdulla AlShamsi Amirmasoud K.Dahaghi Neghabhan S The University of Kansas School of EngineeringChemical and Petroleum Engineering1450 Jayhawk Blvd.Lawrence66045USA

Extensive reviews and cross-comparison studies are essential to analyze the emerging developments in a specific field of *** the past decade,hydrocarbon exploration and exploitation from the shale reservoirs have been the most discussed and researched area around the globe.A dramatic development in shale formations became the game-changer,especially in the *** the other hand,Artificial Intelligence(ai)and Machine Learning(ML)are playing an important role in the rapid development in all the industries through automating most of the routine *** oil industry is also getting equal benefits of ai and ML for the reservoir development planning and its operational accuracy through a series of automated *** the field development,computerized static and dynamic simulation models are generated based on several Petrophysical and Geomechanical properties gathered through different resources that are quite time-taking and *** and ML have made this process much easier,faster,and economical by means of learning through uncounted experiences from already explored and developed reservoirs,their rock properties,and the crossponding fluid flow behavior under different circumstances and hence,predicts *** article provides a comprehensive literature review in the area of ai and ML applications to model Petrophysical and Geomechanical properties using different approaches and ***,a systematic publication counts in each field of subject study per year in different literature databases are presented that infect reflects the trending interest in this ***,multiple ai and ML techniques are discussed in detail which have been tested in the last decade for the sake of achieving higher accuracy in Petrophysical and Geo-Mechanical simulation models.

关键词： ai ML Petrophysics GeoMechanics

Automated Handwriting Recognition and Speech Synthesizer for Indigenous Language Processing

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Computers, Materials & Continua 2022年第8期72卷 3913-3927页

作者： Bassam A.Y.Alqaralleh fahad Aldhaban Feras Mohammed A-Matarneh Esam A.AlQaralleh MIS Department College of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia Department of Computer Science University College of DubaUniversity of Tabuk71491Saudi Arabia School of Engineering Princess Sumaya University for TechnologyAmman11941Jordan

In recent years,researchers in handwriting recognition analysis relating to indigenous languages have gained significant internet among research *** recent developments of artificial intelligence(ai),natural language processing(NLP),and computational linguistics(CL)find useful in the analysis of regional low resource *** lexical task participation might be elaborated to various applications in the *** is apparent from the availability of effective machine recognition models and open access handwritten *** language is a commonly spoken Semitic language,and it is written with the cursive Arabic alphabet from right to *** handwritten Character Recognition(HCR)is a crucial process in optical character *** this view,this paper presents effective Computational linguistics with Deep Learning based Handwriting Recognition and Speech Synthesizer(CLDL-THRSS)for Indigenous *** presented CLDL-THRSS model involves two stages of operations namely automated handwriting recognition and speech ***,the automated handwriting recognition procedure involves preprocessing,segmentation,feature extraction,and ***,the Capsule Network(CapsNet)based feature extractor is employed for the recognition of handwritten Arabic *** optimal hyperparameter tuning,the cuckoo search(CS)optimization technique was included to tune the parameters of the CapsNet ***,deep neural network with hidden Markov model(DNN-HMM)model is employed for the automatic speech *** validate the effective performance of the proposed CLDL-THRSS model,a detailed experimental validation process takes place and investigates the outcomes interms of different *** experimental outcomes denoted that the CLDL-THRSS technique has demonstrated the compared methods.

关键词： Computational linguistics handwriting character recognition natural language processing indigenous language

Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model

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Computers, Materials & Continua 2022年第10期73卷 87-101页

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

Diabetic Retinopathy(DR)has become a widespread illness among diabetics across the *** fundus images are generally used by physicians to detect and classify the stages of *** manual examination of DR images is a time-consuming process with the risks of biased results,automated tools using Artificial Intelligence(ai)to diagnose the disease have become *** this view,the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification(ODL-FDRDC)*** intention of the proposed ODLFDRDC technique is to identify DR and categorize its different grades using retinal fundus *** addition,ODL-FDRDC technique involves region growing segmentation technique to determine the infected ***,the fusion of two DL models namely,CapsNet and MobileNet is used for feature ***,the hyperparameter tuning of these models is also performed via Coyote Optimization Algorithm(COA).Gated Recurrent Unit(GRU)is also utilized to identify *** experimental results of the analysis,accomplished by ODL-FDRDC technique against benchmark DR dataset,established the supremacy of the technique over existing methodologies under different measures.

关键词： Optimization algorithms medical images diabetic retinopathy deep learning fusion model

Artificial lift system optimization using machine learning applications

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Petroleum 2022年第2期8卷 219-226页

作者： fahad I.Syed Mohammed Alshamsi Amirmasoud K.Dahaghi S.Neghabhan University of Kansas&ADNOC Offshore Dept.of Chemical and Petroleum E…Lawrence66045USA

Currently,in the oil industry,artificial lift optimization(ALO)systems are dealing with different applications including well monitor and control,reservoir management,production optimization,predictive maintenance,artificial lift,and flow assurance,multiphase pumping systems,*** scope of this article is to provide a detailed analysis of ALO and predictive pump maintenance applications using machine learning(ML)and artificial intelligence(ai).The oil and gas industry has experienced a lot of improvements that have impacted the businesses and economies associated with the market in recent *** such as unplanned shutdown time and failure of equipment cause a huge impact on many corporations especially with the current fluctuations in hydrocarbon ***,advanced modern technologies such as real-time analysis and predictive maintenance are designed to drive ALO *** paper covers several applications and techniques in which ML and ai have been applied to optimize hydrocarbon withdrawal from potentially depleted reservoirs that require some external supports to uplift the reservoir fluid from sub surface to surface using artificial lift *** a nutshell,the applications of ai and ML for the artificial lift selection,their predictive maintenance,equipment malfunctioning detection,*** a self-trained system are the main topics of this *** reviewing each of these techniques,the workflow is also explained along with the effectiveness of utilizing each application to the current operations.

关键词： Artificial lift optimization Predictive maintenance

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.