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Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

Computers, Materials & Continua 2023年第6期75卷 5379-5393页

作者： Abida Sharif Imran Sharif Muhammad Asim Saleem Muhammad Attique Khan Majed Alhaisoni marriam nawaz Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Faculty of Computing Riphah International UniversityFaisalabadPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science UET TaxilaTaxilaPakistan Department of Software Engineering UET TaxilaTaxilaPakistan Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942KSA Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The Internet of Vehicles(IoV)is a networking paradigm related to the intercommunication of vehicles using a *** a dynamic network,one of the key challenges in IoV is traffic management under increasing vehicles to avoid ***,optimal path selection to route traffic between the origin and destination is *** research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network ***,this work proposed a novel use of the Ant Colony Optimization(ACO)algorithm and formulated the path planning optimization problem as an Integer Linear Program(ILP).This integrates the future estimation metric to predict the future arrivals of the vehicles,searching the optimal *** the mobile nature of IOV,fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal *** model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective ***,this work strongly supports its use in applications having stringent Quality of Service(QoS)requirements for the vehicles.

关键词： Internet of vehicles internet of things fuzzy logic optimization path planning

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Signet Ring Cell Detection from Histological Images Using Deep Learning

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Computers, Materials & Continua 2022年第9期72卷 5985-5997页

作者： Muhammad Faheem Saleem Syed Muhammad Adnan Shah Tahira Nazir Awais Mehmood marriam nawaz Muhammad Attique Khan Seifedine Kadry Arnab Majumdar Orawit Thinnukool Department of Computer Science UETTaxila47050Pakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Civil Engineering Imperial College LondonLondon SW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai 50200Thailand

Signet Ring Cell(SRC)Carcinoma is among the dangerous types of cancers,and has a major contribution towards the death ratio caused by cancerous *** and diagnosis of SRC carcinoma at earlier stages is a challenging,laborious,and costly *** detection of SRCs in a patient’s body through medical imaging by incorporating computing technologies is a hot topic of *** the presented framework,we propose a novel approach that performs the identification and segmentation of SRCs in the histological images by using a deep learning(DL)technique named Mask Region-based Convolutional Neural Network(Mask-RCNN).In the first step,the input image is fed to Resnet-101 for feature *** extracted feature maps are conveyed to Region Proposal Network(RPN)for the generation of the region of interest(RoI)proposals as well as they are directly conveyed to ***,RoIAlign combines the feature maps with RoI proposals and generates segmentation masks by using a fully connected(FC)network and performs classification along with Bounding Box(bb)generation by using FC *** annotations are developed from ground truth(GT)images to perform experimentation on our developed *** introduced approach achieves accurate SRC detection with the precision and recall values of 0.901 and 0.897 respectively which can be utilized in clinical *** aim to release the employed database soon to assist the improvement in the SRC recognition research area.

关键词： Mask RCNN deep learning SRC segmentation

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Brain tumor localization and segmentation using mask RCNN

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Frontiers of Computer Science 2021年第6期15卷 199-201页

作者： Momina MASOOD Tahira NAZIR marriam nawaz Ali JAVED Munwar IQBAL Awais MEHMOOD Department of Computer Science University of Engineering and TechnologyTaxila 47050Pakistan Department of Software Engineering University of Engineering and TechnologyTaxila 47050Pakistan

1 Introduction Brain tumor is a lethal disease affecting millions of people around the globe and has a high mortality *** identification and segmentation of brain tumor helps to increase the survival chances of the patient and also saves them from complex surgical ***,the precise segmentation of brain tumors facilitates the surgeon for better clinical development and cure.

关键词： mortality clinical precise

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Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

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Computers, Materials & Continua 2021年第11期69卷 1927-1944页

作者： marriam nawaz Zahid Mehmood Tahira Nazir Momina Masood Usman Tariq Asmaa Mahdi Munshi Awais Mehmood Muhammad Rashid Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia College of Computer Science and Engineering University of JeddahJeddah21577Saudi Arabia Department of Computer Engineering Umm Al-Qura UniversityMakkah21421Saudi Arabia

Copy-move forgery is the most common type of digital image manipulation,in which the content from the same image is used to forge *** manipulations are performed to hide the desired ***,forgery detection methods are required to identify forged *** have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern(LTrP)features to detect the single and multiple copy-move attacks from the *** proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing *** also uses discrete wavelet transform(DWT)for dimension *** obtained approximate image is distributed into circular blocks on which the LTrP algorithm is employed to calculate the feature vector as the LTrP provides detailed information about the image content by utilizing the direction-based relation of central pixel to its ***,Jeffreys and Matusita distance is used for similarity *** the evaluation of the results,three datasets are used,namely MICC-F220,MICC-F2000,and *** the qualitative and quantitative analysis shows that the proposed method exhibits state-of-the-art performance under the presence of post-processing operations and can accurately locate single and multiple copy-move forgery attacks on the images.

关键词： Copy-move forgery discrete wavelet transform LTrP features image forensic circular blocks

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