检索结果-南通市图书馆

Optimized Two-Level Ensemble Model for Predicting the Parameters of Metamaterial Antenna

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第10期73卷 917-933页

作者： Abdelaziz A.Abdelhamid sultan R.Alotaibi Department of Computer Science College of Computing and Information TechnologyShaqra UniversitySaudi Arabia Department of Computer Science College of Science and HumanitiesShaqra UniversitySaudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityEgypt

Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation *** this paper,we propose a new approach for predicting the bandwidth of metamaterial antenna using a novel ensemble *** proposed ensemble model is composed of two levels of regression *** first level consists of three strong models namely,random forest,support vector regression,and light gradient boosting *** the second level is based on the ElasticNet regression model,which receives the prediction results from the models in the first level for refinement and producing the final optimal *** achieve the best performance of these regression models,the advanced squirrel search optimization algorithm(ASSOA)is utilized to search for the optimal set of hyper-parameters of each *** results show that the proposed two-level ensemble model could achieve a robust prediction of the bandwidth of metamaterial antenna when compared with the recently published ensemble models based on the same publicly available benchmark *** findings indicate that the proposed approach results in root mean square error(RMSE)of(0.013),mean absolute error(MAE)of(0.004),and mean bias error(MBE)of(0.0017).These results are superior to the other competing ensemble models and can predict the antenna bandwidth more accurately.

关键词： Ensemble model parameter prediction metamaterial antenna machine learning model optimization

Enhancing CNN for Forensics Age Estimation Using CGAN and Pseudo-Labelling

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 2499-2516页

作者： sultan Alkaabi Salman Yussof Sameera Al-Mulla Institute of Informatics and Computing in Energy Universiti Tenaga NasionalMalaysia College of Engineering and IT University of DubaiUAE

Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster ***,this process is done manually by human ***,the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and *** improve the recognition speed and consistency,researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network(CNN).CNN requires many training images to obtain high percentage of recognition ***,it is very difficult to get large number of samples of dental images for training the CNN due to the need to comply to privacy acts.A promising solution to this problem is a technique called Generative Adversarial Network(GAN).GAN is a technique that can generate synthetic images that has similar statistics as the training set.A variation of GAN called Conditional GAN(CGAN)enables the generation of the synthetic images to be controlled more precisely such that only the specified type of images will be *** paper proposes a CGAN for generating new dental images to increase the number of images available for training a CNN model to perform age *** also propose a pseudolabelling technique to label the generated images with proper age and *** used the combination of real and generated images to trainDentalAge and Sex Net(DASNET),which is a CNN model for dental age *** on the experiment conducted,the accuracy,coefficient of determination(R2)and Absolute Error(AE)of DASNET have improved to 87%,0.85 and 1.18 years respectively as opposed to 74%,0.72 and 3.45 years when DASNET is trained using real,but smaller number of images.

关键词： Dental forensics age estimation generative adversarial network pseudo-labelling convolutional neural network

Spider monkey optimization based resource allocation and scheduling in fog computing environment

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

高置信计算(英文) 2023年第3期3卷 81-88页

作者： Shahid sultan Hajam Shabir Ahmad Sofi Department of Information Technology National Institute of Technology SrinagarSrinagar 190006India

Spider monkey optimization(SMO)is a quite popular and recent swarm intelligence algorithm for numerical *** is Fission-Fusion social structure based algorithm inspired by spider monkey’s *** algorithm proves to be very efficient in solving various constrained and unconstrained optimization *** paper presents the application of SMO in fog *** propose a heuristic initialization based spider monkey optimization algorithm for resource allocation and scheduling in a fog computing *** algorithm minimizes the total cost(service time and monetary cost)of tasks by choosing the optimal fog *** job fastest processor(LJFP),shortest job fastest processor(SJFP),and minimum completion time(MCT)based initialization of SMO are proposed and compared with each *** performance is compared based on the parameters of average cost,average service time,average monetary cost,and the average cost per *** results demonstrate the efficacy of MCT-SMO as compared to other heuristic initialization based SMO algorithms and Particle Swarm Optimization(PSO).

关键词： Swarm intelligence Spider monkey optimization Fog computing Task scheduling

Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第4期71卷 439-455页

作者： sultan H.Almotiri Mohammed A.Al Ghamdi Computer Science Department College of Computer and Information ScienceUmm AlQura UniversityMakkahKingdom of Saudi Arabia

The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless *** wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network *** schemes estimate the handoff need and cause the network screening process by a single *** strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into *** article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless *** different components the handover need is assessed and the desired network is ***,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a *** proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.

关键词： Wireless sensor networks fuzzy logic AHP-TOPSIS miscellaneous network intelligent computing techniques

An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第1期70卷 1721-1747页

作者： sultan Noman Qasem Mohammed Al-Sarem Faisal Saeed Computer Science Department College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Computer Science Department Faculty of Applied ScienceTaiz UniversityTaiz6803Yemen College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia Information System Department Saba’a Region UniversityMareebYemen

Rumors regarding epidemic diseases such as COVID 19,medicines and treatments,diagnostic methods and public emergencies can have harmful impacts on health and political,social and other aspects of people’s lives,especially during emergency situations and health *** huge amounts of content being posted to social media every second during these situations,it becomes very difficult to detect fake news(rumors)that poses threats to the stability and sustainability of the healthcare sector.A rumor is defined as a statement for which truthfulness has not been *** COVID 19,people found difficulty in obtaining the most truthful news easily because of the huge amount of unverified information on social *** methods have been applied for detecting rumors and tracking their sources for COVID 19-related ***,very few studies have been conducted for this purpose for the Arabic language,which has unique ***,this paper proposes a comprehensive approach which includes two phases:detection and *** the detection phase of the study carried out,several standalone and ensemble machine learning methods were applied on the Arcov-19 dataset.A new detection model was used which combined two models:The Genetic Algorithm Based Support Vector Machine(that works on users’and tweets’features)and the stacking ensemble method(that works on tweets’texts).In the tracking phase,several similarity-based techniques were used to obtain the top 1%of similar tweets to a target tweet/post,which helped to find the source of the *** experiments showed interesting results in terms of accuracy,precision,recall and F1-Score for rumor detection(the accuracy reached 92.63%),and showed interesting findings in the tracking phase,in terms of ROUGE L precision,recall and F1-Score for similarity techniques.

关键词： Rumor detection rumor tracking similarity techniques COVID-19 social media analytics

New Configurations of the Fuzzy Fractional Differential Boussinesq Model with Application in Ocean Engineering and Their Analysis in Statistical Theory

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2023年第11期137卷 1573-1611页

作者： Yu-Ming Chu SaimaRashid Shazia Karim Anam sultan Department of Mathematics Huzhou UniversityHuzhou313000China Department of Mathematics Government College UniversityFaisalabad38000Pakistan Department of Basic Sciences and Humanities UET LahoreFaisalabad CampusLahorePakistan

The fractional-order Boussinesq equations(FBSQe)are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion *** fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition *** also occurs on the sea floor as opposed to at the functionality.A set of dynamical partial differential equations(PDEs)in this article exemplify an unconfined aquifer flow *** can accurately simulate climatological intrinsic waves,so the ripples are spread across a large demographic *** Aboodh transform merged with the mechanism of Adomian decomposition is implemented to obtain the fuzzified FBSQe in R,R^(n) and(2nth)-order involving generalized Hukuhara *** to the system parameter,we classify the qualitative features of the Aboodh transform in the fuzzified Caputo and Atangana-Baleanu-Caputo fractional derivative formulations,which are addressed in *** illustrations depict a comparison analysis between the both fractional operators under gH-differentiability,as well as the appropriate attributes for the fractional-order and unpredictability factorsσ∈[0,1].A statistical experiment is conducted between the findings of both fractional derivatives to prevent changing the hypothesis after the results are *** on the suggested analyses,hydrodynamic technicians,as irrigation or aquifer quality experts,may be capable of obtaining an appropriate storage intensity amount,including an unpredictability threshold.

关键词： Fuzzy set theory aboodh transform adomian decomposition method boussinesq equation fractional derivative operators analysis of variance test

Recapitulation Web 3.0:Architecture,Features and Technologies,Opportunities and Challenges

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第8期37卷 1609-1620页

作者： Amtul Waheed Bhawna Dhupia sultan Mesfer Aldossary Department of Computer Sciences College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Al Dawasir11990Saudi Arabia

Tim Berners-Lee developed the internet at CERN in early 1990 with fundamental technologies such as HTML,URL,and HTTP which became the foundation of the *** contemporary web we use today has been much advanced over a period of time ever since the innovation of the World Wide Web was *** static web was the first version of the web,which was the read-only *** development in web technology is web 3.0 which is a distributed and decentralized web with emerging *** article emphasizes the comparison of important details with the evolution of the *** paper also demonstrates the transactional architecture of DApps in networks and decentralized state ***,connectivity,the semantic web,augmented reality and artificial intelligence are the signifi-cant features of web 3.0 *** features are tremendously used in decision-making on critical issues,which are discussed elaborately in the *** paper provides various technologies to implement web 3.0 *** evolution of web 3.0 brings forth opportunities and *** opportunities are the ownership of the data and a personalized web browsing *** main concerns are security and scalability requirements for blockchain *** article also laid out the challenges that can be considered for further research.

关键词： Web 3.0 DApps Ethereum smart contracts blockchain

PAPR Reduction Using Advanced Partial Transmission Scheme for 5G Waveforms

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第8期42卷 483-492页

作者： Arun Kumar Sumit Chakravarty SSuganya Mehedi Masud sultan Aljahdali Department of Electronics and Communication Engineering JECRC UniversityJaipur303905INDIA Department of Electrical and Computer Engineering Kennesaw State UniversityGAUSA Electronics and Communication Engineering CMR Institute of TechnologyBangaloreINDIA Department of Computer Science College of Computers and Information TechnologyTaif University11099Saudi Arabia

The implementation of Peak Average to Power Ratio(PAPR)reduction technologies will play an important role in the regularization of Fifth Generation(5G)radio *** reduction in the advanced waveform will be the key part of designing a 5G network for different *** work introduces the simulation of an Advanced Partial Transmission Sequence(A-PTS)reduction techniques for Orthogonal Frequency Division Multiplexing(OFDM)and Filter Bank Multi-Carrier(FBMC)transmission *** the projected A-PTS,the FBMC signals are mapped into the number of sub-blocks and Inverse Fast Fourier transform(IFFT)is performed to estimate the high peak power in the time *** FBMC sub-blocks are multiplied with the phase elements to achieve an optimal PAPR value.A MATLAB 2014v simulation is used to estimate the PAPR,Bit Error Rate(BER),Error Vector Magnitude(EVM),and Modulation Error Rate(MER)performance of the proposed reduction *** simulated result reveals that the performance of the projected algorithm is better than the conventional algorithms.

关键词： PAPR PTS OFDM FBMC 5G

Prediction of Covid-19 Based on Chest X-Ray Images Using Deep Learning with CNN

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第6期41卷 1223-1240页

作者： Anika Tahsin Meem Mohammad Monirujjaman Khan Mehedi Masud sultan Aljahdali Department of Electrical and Computer Engineering North South UniversityBashundharaDhaka1229Bangladesh Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

The COVID-19 pandemic has caused trouble in people’s daily lives andruined several economies around the world, killing millions of people thus far. Itis essential to screen the affected patients in a timely and cost-effective manner inorder to fight this disease. This paper presents the prediction of COVID-19 withChest X-Ray images, and the implementation of an image processing systemoperated using deep learning and neural networks. In this paper, a Deep Learning,Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed. In this study, machine learning tools such as TensorFlow were used forbuilding and training neural nets. Scikit-learn was used for machine learning fromend to end. Various deep learning features are used, such as Conv2D, Dense Net,Dropout, Maxpooling2D for creating the model. The proposed approach had aclassification accuracy of 96.43 percent and a validation accuracy of 98.33 percentafter training and testing the X-Ray pictures. Finally, a web application has beendeveloped for general users, which will detect chest x-ray images either as covidor normal. A GUI application for the Covid prediction framework was run. Achest X-ray image can be browsed and fed into the program by medical personnelor the general public.

关键词： Covid-19 prediction covid-19 coronavirus normal deep learning convolutional neural network image processing chest x-ray