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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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Hyperspectral Image Classification Method Based on Global Space-Spectral Attention Mechanism

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Journal of Shanghai Jiaotong University (science) 2025年 1-11页

作者： Qin, Rui Wu, Benze Liu, Xinfu Wu, Yirui College of Computer Science and Software Engineering Hohai University Nanjing211100 China Nangjing Research Institute of Electronic Engineering Nanjing210007 China College of Artificial Intelligence and Automation Hohai University Jiangsu Changzhou213200 China

In hyperspectral remote sensing imagery, pixel interactions within defined spatial extents result in the mixing of adjacent pixels. Additionally, the high similarity of adjacent spectra leads to information redundancy, which hinders the extraction of global spatial and spectral correlations. In order to solve the problems of mixed adjacent pixels and redundant adjacent spectra, this work offers a hyperspectral image classification approach that uses a global space-spectral attention mechanism. First, the proposed method’s global spatial attention module uses multi-scale dilated convolution to produce a bigger receptive field to be capable of capturing global spatial correlation and obtain unmixed pixel information. Then, the global spectral attention module designs a spectral domain partition algorithm, using the combination of regional density as well as information entropy as the threshold to divide spectrum into dispersed subsets and eliminate redundant information. The global context information for entire spectral band is fully exploited, and correlation of the global spectral information is extracted. Finally, the two modules combine to provide a global correlation of space and spectrum. Experiments demonstrate that the suggested method obtains overall accuracies of 97.28%, 94.73%, and 95.76% on the three WHU-Hi hyperspectral datasets, surpassing comparison methods. © Shanghai Jiao Tong University 2024.

关键词： Pixels

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A dynamic and resource sharing virtual network mapping algorithm

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Digital Communications and Networks 2023年第5期9卷 1101-1112页

作者： Xiancui Xiao Xiangwei Zheng Ji Bian Cun Ji Xinchun Cui School of Information Science and Engineering Shandong Normal UniversityJinan250014China School of Information Engineering Shandong Management UniversityJinan250358China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014China School of Computer Science and Technology Qufu Normal UniversityRizhao276800China

Network virtualization can effectively establish dedicated virtual networks to implement various network ***,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and *** addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation *** on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology *** the node mapping process,three properties of the node are used to measure its mapping ***,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link ***,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource *** former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision *** results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenu

关键词： Network virtualization VNRs Network frameworks Dynamic resource allocation Resource sharing

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Development of Classification Model based on Arabic Textual Analysis to Detect Fake News: Case Studies 1

Development of Classification Model based on Arabic Textual ...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Himdi, Hanen Tarik Assiri, Fatmah Yousef University of Jeddah College of Computer Science and Engineering Computer Science and Artificial Intelligence Department Jeddah Saudi Arabia University of Jeddah College of Computer Science and Engineering Software Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

The ease of communication that has been made possible by chat messaging platforms, such as WhatsApp and Line, and their increased use and ubiquity in society, have motivated purveyors of fake news to create and present their news as legitimate. Though different organisations continued their efforts to resolve this problem, many of the developed solutions rely on verifying the associated metadata, which are not always available. Several studies have attempted to identify fake news by analysing textual content;however, there is a lack of studies on Arabic language sources. Our work filled this gap;we proposed a machine learning model that classifies Arabic fake news based on textual analysis. This paper shows the feasibility of our approach to classify Arabic text in social media applications. © 2023 IEEE.

关键词： Machine learning

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Water Quality Monitoring System for Nile Tilapia Farming Using LoRa Technology 8

Water Quality Monitoring System for Nile Tilapia Farming Usi...

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8th International Conference on Information Technology, InCIT 2024

作者： Chansiri, Nawara Sangkaphet, Ponglert Chaleamwong, Buppawan Kaewklom, Chaivichit Makdee, Supawee Ubon Ratchathani Rajabhat University Faculty of Computer Science Department of Software Engineering Ubon Ratchathani Thailand Ubon Ratchathani Rajabhat University Faculty of Computer Science Department of Computer Science Ubon Ratchathani Thailand

ISBN: (纸本)9798350366303

Fish farmers operating at Sirindhorn Dam in Ubon Ratchathani have faced significant challenges, including high mortality rates attributable to unstable weather conditions that compromise water quality. To tackle these issues, the Internet of Things has emerged as a tool to enhance aquaculture management. This research seeks to develop a prototype water quality monitoring system using LoRa technology to facilitate data transmission between sensor nodes in a peer-to-peer configuration. The development and testing of the system demonstrate its ability to accurately monitor key water quality parameters, including dissolved oxygen, pH, and water temperature, while allowing for remote data transmission. This research involved a sample group of five program development experts and 15 general users, with various tools employed for system efficiency assessment. A statistical analysis including the mean and standard deviation was performed to evaluate performance. The findings reveal a high overall efficiency assessment, with an average score of 4.43. © 2024 IEEE.

关键词： Efficiency

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Transaction transmission model for blockchain channels based on non-cooperative games

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science China(Information sciences) 2023年第1期66卷 97-114页

作者： Peiyun ZHANG Chenxi LI Mengchu ZHOU Wenjun HUANG Abdullah ABUSORRAH Omaimah O.BAMASAG Engineering Research Center of Digital Forensics of Ministry of Education School of Computer and SoftwareNanjing University of Information Science and Technology School of Computer and Information Anhui Normal University Department of Electrical and Computer Engineering New Jersey Institute of Technology Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering and K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University Department of Computer Science Faculty of Computing and Information Technology Center of Excellence in Smart Environment Research King Abdulaziz University

In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.

关键词： Blockchain channel transaction transmission channel balance channel state channel transmission probability non-cooperative game

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M-GhostNet: A Lightweight CNN Model Combined with Coordinate Attention Mechanism for Identifying Pests and Diseases 12

M-GhostNet: A Lightweight CNN Model Combined with Coordinate...

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12th International Conference on Computing and Pattern Recognition, ICCPR 2023

作者： Ma, Chi Xiao, Yu Hu, Hui Li, Jingyan Wu, Jie The School of Computer Science and Engineering Huizhou University Huizhou516007 China The School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

ISBN: (纸本)9798400707988

Plant pests and diseases have always been an important factor affecting agricultural production, and how to automatically identify them is one of the current research hotspots. Although traditional deep learning models can achieve good results, they are difficult to deploy into small devices due to their large number of parameters. In this paper, we design a lightweight convolutional neural network M-GhostNet based on the coordinate attention mechanism, which improves the bottleneck structure in the original GhostNet and and effectively extracts the spatial information of the image. We compare and ablate the M-GhostNet model on the IP102 dataset and the Embrapa dataset. Compared with the existing lightweight neural networks, M-GhostNet achieves the best results of 67.15%, 65.04%, and 71.41% on the IP102 dataset, respectively, and 92.67%, 95.65%, 93.74%, and 96.52% on the Embrapa dataset in terms of Mrec, Mpre, MF1, and Acc. The final results show that M-GhostNet can achieve good performance in both pest and disease identification. © 2023 ACM.

关键词： Convolutional neural networks

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Generative AI — The End of Systematic Reviews in PhD Projects?

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ACM Inroads 2024年第2期15卷 48-50页

作者： Zamani, Sanaz Sinha, Roopak Department of Computer Science and Software Engineering Auckland University of Technology Auckland New Zealand School of Information Technology Deakin University Melbourne Australia

In this opinion piece, we question the efficacy of students conducting systematic reviews (SRs) at the very start of their PhDs, especially now that we are riding, or drowning in, the Generative AI wave. How would the ubiquitous availability of Generative AI tools shape PhD research and supervision, and how can we capitalize on such disruptions? We report our reflections about early-stage PhD research from 10+ PhD supervisions completed by Sinha, and a recently started PhD project with Zamani as the student. We conducted a systematic literature review following traditional methods for the first four months and then revisited the task using ChatGPT and other related tools. We opine that while SRs still have value for new students, Generative AI must be incorporated, with care, to significantly enhance student learning, reinvest time savings into other, often-ignored skills, and improve the quality (breadth and depth) of SRs. © 2024 Association for Computing Machinery. All rights reserved.

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The role of ChatGPT in sports trauma: a mini review on strengths and limits of open AI application

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Discover Artificial Intelligence 2023年第1期3卷 40页

作者： Hasnain, Muhammad Mehboob, Bilal Imran, Shahid Department of Computer Science Lahore Leads University Lahore54000 Pakistan Department of Software Engineering Superior University Lahore Lahore54000 Pakistan

Purpose: This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. The objective of this study is to present an overview of the literature on how ChatGPT handles information about sports trauma, considering both its strengths and limitations. Methods: A review method is used in this study. Well-known online databases such as PubMed, scienceDirect, Springer and Google Scholar were searched for the relevant studies. In addition, ChatGPT application was accessed to provide the concise information on the research topic. Results: Search strategy resulted in 30 articles on the topic. Among them only seven studies revealed the potential applications of ChatGPT in sports. The other five studies presented the current status on ChatGPT and sports trauma. The results show that ChatGPT generates information on several types of sports trauma that align with the published literature. However, some limitations of ChatGPT are identified such as its tendency to provide general information about sprains and lack of updated statistics on sports trauma. This study also identified some serious concerns such ethical considerations, data privacy and security regarding the ChatGPT application in sports industry. Conclusion: Despite having some limitations, the ChatGPT application has potential to be used in healthcare, and particularly in sports trauma. The implications of this study guide scholars for the development of enhanced AI systems, which are tailored to redress the challenges of sports trauma. © The Author(s) 2023.

关键词： Sports

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A Fast Panoptic Segmentation Network for Self-Driving Scene Understanding

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computer Systems science & engineering 2022年第10期43卷 27-43页

作者： Abdul Majid Sumaira Kausar Samabia Tehsin Amina Jameel Department of Computer Science Bahiria UniversityIslamabadPakistan Department of Software Engineering Bahiria UniversityKarachiPakistan

In recent years,a gain in popularity and significance of science understanding has been observed due to the high paced progress in computer vision techniques and *** primary focus of computer vision based scene understanding is to label each and every pixel in an image as the category of the object it belongs *** it is required to combine segmentation and detection in a single *** many successful computer vision methods has been developed to aid scene understanding for a variety of real world *** understanding systems typically involves detection and segmentation of different natural and manmade things.A lot of research has been performed in recent years,mostly with a focus on things(a well-defined objects that has shape,orientations and size)with a less focus on stuff classes(amorphous regions that are unclear and lack a shape,size or other characteristics Stuff region describes many aspects of scene,like type,situation,environment of scene *** hence can be very helpful in scene *** methods for scene understanding still have to cover a challenging path to cope up with the challenges of computational time,accuracy and robustness for varying level of scene complexity.A robust scene understanding method has to effectively deal with imbalanced distribution of classes,overlapping objects,fuzzy object boundaries and poorly localized *** proposed method presents Panoptic Segmentation on Cityscapes ***-V2 is used as a backbone for feature extraction that is pre-trained on ***-V2 with state-of-art encoder-decoder architecture of DeepLabV3+with some customization and optimization is employed Atrous convolution along with Spatial Pyramid Pooling are also utilized in the proposed method to make it more accurate and *** promising and encouraging results have been achieved that indicates the potential of the proposed method for robust scene understanding in a fast and

关键词： Panoptic segmentation instance segmentation semantic segmentation deep learning computer vision scene understanding autonomous applications atrous convolution

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