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real-time Privacy Preserving Framework for Covid-19 Contact Tracing

Computers, Materials & Continua 2022年第1期70卷 1017-1032页

作者： Akashdeep Bhardwaj Ahmed A.mohamed Manoj Kumar Mohammed Alshehri Ahed Abugabah School of Computer Science University of Petroleum&Energy Studies(UPES)Dehradun248007India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information Technology Faculty of Computer and InformationAssiut UniversityAssiut71515Egypt Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information System College of Technological InnovationZayed UniversityAbu DhabiUnited Arab Emirates

The recent unprecedented threat from COVID-19 and past epidemics,such as SArS,AIDS,and Ebola,has affected millions of people in multiple *** have shut their borders,and their nationals have been advised to *** variety of responses to the pandemic has given rise to data privacy *** prevention and control strategies as well as disease control measures,especially real-time contact tracing for COVID-19,require the identification of people exposed to *** tracing frameworks use mobile apps and geolocations to trace ***,while the motive may be well intended,the limitations and security issues associated with using such a technology are a serious cause of *** are growing concerns regarding the privacy of an individual’s location and personal identifiable information(PII)being shared with governments and/or health *** study presents a real-time,trust-based contact-tracing framework that operateswithout the use of an individual’sPII,location sensing,or gathering GPS *** focus of the proposed contact tracing framework is to ensure real-time privacy using the Bluetooth range of individuals to determine others within the *** research validates the trust-based framework using Bluetooth as practical and *** our proposed methodology,personal information,health logs,and location data will be secure and not *** research analyzes 100,000 tracing dataset records from 150 mobile devices to identify infected users and active users.

关键词： Privacy contact tracing mobile apps Bluetooth Covid epidemic

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Improved Hybrid Swarm Intelligence for Optimizing the Energy in WSN

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Computer Systems Science & Engineering 2023年第8期46卷 2527-2542页

作者： Ahmed Najat Ahmed JinHyung Kim Yunyoung Nam mohamed Abouhawwash Department of Computer Engineering Lebanese French UniversityErbil44001Iraq B LIFE Inc. Suwon16463Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

In this current century,most industries are moving towards automation,where human intervention is dramatically *** revolution leads to industrial revolution 4.0,which uses the Internet of Things(IoT)and wireless sensor networks(WSN).With its associated applications,this IoT device is used to compute the receivedWSN data from devices and transfer it to remote locations for *** general,WSNs,the gateways are a long distance from the base station(BS)and are communicated through the gateways nearer to the *** the gateway,which is closer to the BS,energy drains faster because of the heavy load,which leads to energy issues around the *** the sensors are battery-operated,either replacement or recharging of those sensor node batteries is not possible after it is deployed to their corresponding *** that situation,energy plays a vital role in sensor *** reducing the network energy consumption and increasing the network lifetime,this paper proposed an efficient cluster head selection using Improved Social spider Optimization with a rough Set(ISSrS)and routing path selection to reduce the network load using the Improved Grey wolf optimization(IGWO)approach.(i)Using ISSrS,the initial clusters are formed with the local nodes,and the cluster head is chosen.(ii)Load balancing through routing path selection using *** simulation results prove that the proposed optimization-based approaches efficiently reduce the energy through load balancing compared to existing systems in terms of energy efficiency,packet delivery ratio,network throughput,and packet loss percentage.

关键词： Wireless sensor networks(WSN) internet of things(IoT) energy efficiency load balance sensors grey wolf optimization social spider optimization

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Manta ray Foraging Optimization with Machine Learning Based Biomedical Data Classification

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Computers, Materials & Continua 2022年第11期73卷 3275-3290页

作者： Amal Al-rasheed Jaber S.Alzahrani Majdy M.Eltahir Abdullah mohamed Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani mohamed I.Eldesouki Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various *** developments of artificial intelligence(AI)and machine learning(ML)models assist in the effectual design of medical data classification ***,this article concentrates on the development of optimal Stacked Long Short Term Memory Sequence-toSequence Autoencoder(OSAE-LSTM)model for biomedical data *** presented OSAE-LSTM model intends to classify the biomedical data for the existence of ***,the OSAE-LSTM model involves min-max normalization based pre-processing to scale the data into uniform *** by,the SAE-LSTM model is utilized for the detection and classification of diseases in biomedical *** last,manta ray foraging optimization(MrFO)algorithm has been employed for hyperparameter optimization *** utilization of MrFO algorithm assists in optimal selection of hypermeters involved in the SAE-LSTM *** simulation analysis of the OSAE-LSTM model has been tested using a set of benchmark medical datasets and the results reported the improvements of the OSAELSTM model over the other approaches under several dimensions.

关键词： Biomedical data classification deep learning manta ray foraging optimization healthcare machine learning artificial intelligence

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Metaheuristic with Deep Learning Enabled Biomedical Bone Age Assessment and Classification Model

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Computers, Materials & Continua 2022年第12期73卷 5473-5489页

作者： Mesfer Al Duhayyim Areej A.Malibari Marwa Obayya mohamed K.Nour Ahmed S.Salama mohamed I.Eldesouki Abu Sarwar Zamani Mohammed rizwanullah Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The skeletal bone age assessment(BAA)was extremely implemented in development prediction and auxiliary analysis of medicinal issues.X-ray images of hands were detected from the estimation of bone age,whereas the ossification centers of epiphysis and carpal bones are important *** typical skeletal BAA approaches remove these regions for predicting the bone age,however,few of them attain suitable efficacy or *** BAA techniques with deep learning(DL)methods are reached the leading efficiency on manual and typical ***,this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with deep learning(ISBAAC-MDL)*** presented ISBAAC-MDL technique majorly focuses on the identification of bone age prediction and classification *** attain this,the presented ISBAAC-MDL model derives a mask region-related Convolutional Neural Network(Mask-rCNN)with MobileNet as baseline model to extract *** by,the whale optimization algorithm(WOA)is implemented for hyperparameter tuning of the MobileNet *** last,Deep Feed-Forward Module(DFFM)based age prediction and radial Basis Function Neural Network(rBFNN)based stage classification approach is *** experimental evaluation of the ISBAAC-MDL model is tested using benchmark dataset and the outcomes are assessed over distinct *** experimental outcomes reported the better performances of the ISBAACMDL model over recent approaches with maximum accuracy of 0.9920.

关键词： Biomedical images bone age assessment age prediction computer vision deep learning image classification

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The role and potential of attapulgite in catalytic pyrolysis of refinery waste activated sludge

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Petroleum Science 2022年第1期19卷 354-362页

作者： Qinghong Wang Kanghong Hao Chelsea Benally Yue Kou Zhexuan An mohamed Gamal El-Din Chunmao Chen State Key Laboratory of Heavy Oil Processing Beijing Key Laboratory of Oil and Gas Pollution ControlChina University of Petroleum-BeijingBeijing102249China Department of Civil and Environmental Engineering University of AlbertaEdmontonAlbertaT6G 1H9Canada

Pyrolysis is a promising technology for the treatment of refinery waste activated sludge(rWAS).In this study,attapulgite as a natural clay was used to enhance the pyrolysis of *** yields,characteristics of pyrolytic products,pyrolytic kinetics and mechanisms were *** attapulgite improved the conversion of rWAS into non-condensable gases and pyrolytic *** bio-oil quality improved and the biochar yield *** average activation energy of Stage Ⅰ(230-400℃)and Stage Ⅱ(400-500℃)decreased by 36.5%and 49.7%,respectively,compared to rWAS ***_(2)O_(3)and Fe_(2)O_(3)in attapulgite enhanced the dealkylation reaction and cracking of C-C *** content of the gasoline(raction of bio-oil doubled relative to rWAS *** promoted the deoxygenation,dehydroxylation and dehydrogenation reactions of O-containing compounds,and the content of CO and CO_(2) in non-condensable gases *** of attapulgite(rWAS:attapulgite ratio of 1:1)decreased the O mobility from 14.6%to 12.8%relative to rWAS ***,the content of saturates in bio-oil increased from 38.5 wt%to 47.2 wt%and the lower heating value(LHV)increased from 6.8 kcal/kg to 8.4 kcal/*** heavy metals originally in rWAS were fixed into the pyrolytic residue and the environmental risks are *** study demonstrates the role and potential of attapulgite in catalytic pyrolysis of rWAS with an added advantage of increased cost-effectiveness.

关键词： Catalytic pyrolysis Attapulgite Kinetics Product characteristics

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Blockchain Driven Metaheuristic route Planning in Secure Wireless Sensor Networks

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Computers, Materials & Continua 2023年第1期74卷 933-949页

作者： M.V.rajesh T.Archana Acharya Hafis Hajiyev E.Laxmi Lydia Haya Mesfer Alshahrani mohamed K Nour Abdullah mohamed Mesfer Al Duhayyim Department of Computer Science and Engineering Aditya Engineering CollegeSurampalem533437India Department of Business Administration Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Accounting and Audit Azerbaijan State University of Economics(UNEC)BakuRepublic of Azerbaijan Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

recently,Internet of Things(IoT)has been developed into a field of research and it purposes at linking many sensors enabling devices mostly to data collection and track *** sensor network(WSN)is a vital element of IoT paradigm since its inception and has developed into one of the chosen platforms for deploying many smart city application regions such as disaster management,intelligent transportation,home automation,smart buildings,and other such IoT-based *** routing approaches were extremely-utilized energy efficient approaches with an initial drive that is,for balancing the energy amongst sensor *** clustering and routing procedures assumed that Non-Polynomial(NP)hard problems but bio-simulated approaches are utilized to a recognized time for resolving such *** this motivation,this paper presents a new blockchain with Enhanced Hunger Games Search based route Planning(BCEHGS-rP)scheme for IoT assisted *** presented BCEHGS-rP model majorly employs BC technology for secure communication in the IoT supportedWSN *** addition,an effective multihop route planning approach was designed by the use of EHGS *** proposed EHGS technique is derived from the concept of Hill Climbing strategy(HCS)and HGS ***,a fitness function with two parameters namely residual energy(rE)and intercluster distance to elect optimal *** performance validation of the BCEHGS-rP model is experimented with under diverse number of *** experimental outcomes highlighted the better performance of the BCEHGS-rP technique on recent approaches.

关键词： Internet of things wireless sensor networks routing metaheuristics blockchain

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Investigation of new solutions for an extended(2+1)-dimensional Calogero-Bogoyavlenskii-Schif equation

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Frontiers of Mathematics in China 2021年第4期16卷 925-936页

作者： mohamed r.ALI r.SADAT Wen-Xiu MA Department of Mathematics Faculty of EngineeringBenha UniversityEgypt Department of Mathematics Zagazig Faculty of EngineeringZagazig UniversityZagazigEgypt Department of Mathematics Zhejiang Normal UniversityJinhua 321004China Department of Mathematics King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics and Statistics University of South FloridaTampaFL33620-5700USA School of Mathematics South China University of TechnologyGuangzhou 510640China School of Mathematical and Statistical Sciences North-West UniversityMafikeng CamusPrivate Bag X2046Mmabatho 2735South Africa

We investigate and concentrate on new infinitesimal generators of Lie symmetries for an extended(2+1)-dimensional Calogero-Bogoyavlenskii-Schif(eCBS)equation using the commutator table which results in a system of nonlinear ordinary differential equations(ODEs)which can be manually *** two stages of Lie symmetry reductions,the eCBS equation is reduced to non-solvable nonlinear ODEs using different combinations of optimal Lie *** the integration method and the riccati and Bernoulli equation methods,we investigate new analytical solutions to those *** substituting to the original variables generates new solutions to the eCBS *** results are simulated through three-and two-dimensional plots.

关键词： Extended Calogero-Bogoyavlenskii-Schif(eCBS)equation riccati-Bernoulli equation symmetry analysis integrating factor nonlinear integrable equations

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Modified aquila optimizer for forecasting oil production

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Geo-Spatial Information Science 2022年第4期25卷 519-535页

作者： Mohammed A.A.Al-qaness Ahmed A.Ewees Hong Fan Ayman Mutahar Alrassas mohamed Abd Elaziz State Key Laboratory for Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Systems University of Bisha Department of e-BishaKingdom of Saudi Arabia Department of Computer Damietta UniversityDamiettaEgypt School of Petroleum Engineering China University of Petroleum(East China)QingdaoChina Department of Mathematics Faculty of ScienceZagazig UniversityZagazigEgypt Artificial Intelligence research Center(AIrC) Ajman UniversityAjman 346United Arab Emirates Faculty of Computer Science&Engineering Galala UniversitySuze 435611Egypt

Oil production estimation plays a critical role in economic plans for local governments and ***,many studies applied different Artificial Intelligence(AI)based meth-ods to estimate oil production in different *** Adaptive Neuro-Fuzzy Inference System(ANFIS)is a well-known model that has been successfully employed in various applica-tions,including time-series ***,the ANFIS model faces critical shortcomings in its parameters during the configuration *** this point,this paper works to solve the drawbacks of the ANFIS by optimizing ANFIS parameters using a modified Aquila Optimizer(AO)with the Opposition-Based Learning(OBL)*** main idea of the developed model,AOOBL-ANFIS,is to enhance the search process of the AO and use the AOOBL to boost the performance of the *** proposed model is evaluated using real-world oil produc-tion datasets collected from different oilfields using several performance metrics,including root Mean Square Error(rMSE),Mean Absolute Error(MAE),coefficient of determination(r2),Standard Deviation(Std),and computational ***,the AOOBL-ANFIS model is compared to several modified ANFIS models include Particle Swarm Optimization(PSO)-ANFIS,Grey Wolf Optimizer(GWO)-ANFIS,Sine Cosine Algorithm(SCA)-ANFIS,Slime Mold Algorithm(SMA)-ANFIS,and Genetic Algorithm(GA)-ANFIS,***,it is compared to well-known time series forecasting methods,namely,Autoregressive Integrated Moving Average(ArIMA),Long Short-Term Memory(LSTM),Seasonal Autoregressive Integrated Moving Average(SArIMA),and Neural Network(NN).The outcomes verified the high performance of the AOOBL-ANFIS,which outperformed the classic ANFIS model and the compared models.

关键词： Oil production ANFIS opposition-based learning(OBL) Aquila Optimizer(AO) time series forecasting Tahe oilfield Sunah oilfield

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EJUSTCO:Monte Carlo radiation transport code hybrid with ANN model for gamma-ray shielding simulation

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Nuclear Science and Techniques 2023年第9期34卷 155-176页

作者： Joseph Konadu Boahen Ahmed S.G.Khalil Mohsen A.Hassan Samir A.Elsagheer mohamed Materials Science and Engineering Department School of Innovative Design EngineeringEgypt-Japan University of Science and Technology(E-JUST)179New Borg El-Arab CityEgypt Physics Department Environmental and Smart Technology GroupFaculty of ScienceFayoum UniversityFayoum 63514Egypt Faculty of Engineering Aswan UniversityAswanEgypt

Gamma ray shielding is essential to ensure the safety of personnel and equipment in facilities and environments where radiation *** Monte Carlo technique is vital for analyzing the gamma-ray shielding capabilities of *** this study,a simple Monte Carlo code,EJUSTCO,is developed to cd simulate gamma radiation transport in shielding materials for academic *** code considers the photoelectric effect,Compton(incoherent)scattering,pair production,and photon annihilation as the dominant interaction mechanisms in the gamma radiation shielding *** reduction techniques,such as the russian roulette,survival weighting,and exponential transformation,are incorporated into the code to improve computational *** the exponential transformation parameter typically requires trial and error as well as ***,a deep learning neural network is proposed as a viable method for predicting this parameter for the first *** model achieves an MSE of 0.00076752 and an r-value of *** exposure buildup factors and radiation dose rates due to the passage of gamma radiation with different source energies and varying thicknesses of lead,water,iron,concrete,and aluminum in single-,double-,and triple-layer material systems are validated by comparing the results with those of MCNP,ESG,ANS-6.4.3,MCBLD,MONTErEY MArK(M),PENELOPE,and *** errors of 5.6%,2.75%,and 10%are achieved for the exposure buildup factor in single-,double-,and triple-layer materials,respectively.A significant parameter that is not considered in similar studies is the gamma ray *** the EJUSTCO code,the total number and energy albedos have been *** results are compared with those of MCNP,FOTELP,and *** general,the EJUSTCO-developed code can be employed to assess the performance of radiation shielding materials because the validation results are consistent with theoretical,experimental,and literary results.

关键词： Monte Carlo Gamma rays Shielding Artificial neural network Simulation

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Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

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Intelligent Automation & Soft Computing 2023年第6期36卷 3121-3137页

作者： Najm Alotaibi Badriyya B.Al-onazi mohamed K.Nour Abdullah mohamed Abdelwahed Motwakel Gouse Pasha Mohammed Ishfaq Yaseen Mohammed rizwanullah Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh13369Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia

Opinion Mining(OM)studies in Arabic are limited though it is one of the most extensively-spoken languages *** the interest in OM studies in the Arabic language is growing among researchers,it needs a vast number of investigations due to the unique morphological principles of the *** OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic *** comparative OM studies in the English language are wide and ***,comparative OM studies in the Arabic language are yet to be established and are still in a nascent *** unique features of the Arabic language make it essential to expand the studies regarding the Arabic *** contains unique featuressuchasdiacritics,elongation,*** study proposes a Political Optimizer with Probabilistic Neural Network-based Comparative Opinion Mining(POPNN-COM)model for the Arabic *** proposed POPNN-COM model aims to recognize comparative and non-comparative texts in Arabic in the context of social ***,the POPNN-COM model involves different levels of data pre-processing to transform the input data into a useful ***,the pre-processed data is fed into the PNN model for classification and recognition of the data under different class *** last,the PO algorithm is employed for fine-tuning the parameters involved in this model to achieve enhanced *** proposed POPNN-COM model was experimentally validated using two standard datasets,and the outcomes established the promising performance of the proposed POPNN-COM method over other recent approaches.

关键词： Comparative opinion mining Arabic text social media parameter tuning machine learning political optimizer

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