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Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

computers, Materials & Continua 2024年第1期78卷 1461-1479页

作者： Sarah Mustafa Eljack Mahdi Jemmali Mohsen Denden Mutasim Al Sadig Abdullah M.Algashami Sadok Turki Department of Computer Science and Information College of Science at ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjahUnited Arab Emirates Higher Institute of Computer Science and Mathematics University of MonastirMonastir5000Tunisia Mars Laboratory University of SousseSousseTunisia Department of Logistic and Maintenance UFR MIM at MetzUniversity of LorraineMetzFrance Department of Computer and Information Technologies College of Telecommunicationand Information Riyadh CTITechnical and Vocational Training Corporation TVTCRiyadh12464Saudi Arabia Department of Computer Science Higher Institute of Applied Sciences of SousseSousse UniversitySousse4000Tunisia

In the cloud environment,ensuring a high level of data security is in high *** planning storage optimization is part of the whole security process in the cloud *** enables data security by avoiding the risk of data loss and data *** development of data flow scheduling approaches in the cloud environment taking security parameters into account is *** our work,we propose a data scheduling model for the cloud *** is made up of three parts that together help dispatch user data flow to the appropriate *** first component is the Collector Agent whichmust periodically collect information on the state of the network *** second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the *** third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable *** should be noted that each part of the proposedmodel requires the development of its *** this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link *** algorithms are based on the grouping of transmitted files and the iterative *** proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)*** experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

关键词： Cyber-security cloud computing cloud security algorithms heuristics

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Drone-Based Public Surveillance Using 3D Point Clouds and Neuro-Fuzzy Classifier

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computers, Materials & Continua 2025年第3期82卷 4759-4776页

作者： Yawar Abbas Aisha Ahmed Alarfaj Ebtisam Abdullah Alabdulqader Asaad Algarni Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea Cognitive Systems Lab University of BremenBremen28359Germany

Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera *** research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)*** first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale *** YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further *** joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are *** features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity ***-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing *** particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.

关键词： Activity recognition geodesic distance pattern recognition neuro fuzzy classifier

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Machine Learning-Based Routing Protocol in Flying Ad Hoc Networks: A Review

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computers, Materials & Continua 2025年第2期82卷 1615-1643页

作者： Priyanka Manjit Kaur Deepak Prashar Leo Mrsic Arfat Ahmad Khan Department of Computer Science and Engineering(CSE) Lovely Professional UniversityPhagwara144411India Department for Program Engineering Algebra UniversityGradiscanska 24Zagreb10000Croatia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

“Flying Ad Hoc Networks(FANETs)”,which use“Unmanned Aerial Vehicles(UAVs)”,are developing as a critical mechanism for numerous applications,such as military operations and civilian *** dynamic nature of FANETs,with high mobility,quick node migration,and frequent topology changes,presents substantial hurdles for routing protocol *** the preceding few years,researchers have found that machine learning gives productive solutions in routing while preserving the nature of FANET,which is topology change and high *** paper reviews current research on routing protocols and Machine Learning(ML)approaches applied to FANETs,emphasizing developments between 2021 and *** research uses the PRISMA approach to sift through the literature,filtering results from the SCOPUS database to find 82 relevant *** research study uses machine learning-based routing algorithms to beat the issues of high mobility,dynamic topologies,and intermittent connection in *** compared with conventional routing,it gives an energy-efficient and fast decision-making solution in a real-time environment,with greater fault tolerance *** protocols aim to increase routing efficiency,flexibility,and network stability using ML’s predictive and adaptive *** comprehensive review seeks to integrate existing information,offer novel integration approaches,and recommend future research topics for improving routing efficiency and flexibility in ***,the study highlights emerging trends in ML integration,discusses challenges faced during the review,and discusses overcoming these hurdles in future research.

关键词： FANET protocol machine learning

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Deep Learning Approach for Hand Gesture Recognition:Applications in Deaf Communication and Healthcare

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computers, Materials & Continua 2024年第1期78卷 127-144页

作者： Khursheed Aurangzeb Khalid Javeed Musaed Alhussein Imad Rida Syed Irtaza Haider Anubha Parashar Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Kingdom of Saudi Arabia Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France Department of Computer Science and Engineering Manipal University JaipurJaipur303007India

Hand gestures have been used as a significant mode of communication since the advent of human *** facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free *** technology is pivotal in healthcare and communication for the deaf *** significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature ***,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and ***,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer *** proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)Alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,*** results demonstrate the effectiveness of CNN as a promising HGRoc *** findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.

关键词： computer vision deep learning gait recognition sign language recognition machine learning

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Jointly Preserving Subject and Object Anonymity in Nearby Friends Querying for Curious Service Providers

Jointly Preserving Subject and Object Anonymity in Nearby Fr...

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Abul, Osman Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Computer Engineering TOBB University of Economics and Technology Ankara Ankara Turkey

ISBN: (纸本)9798400716928

This work studies the urban area location privacy preserving location updates and nearby friends (NF) querying for the centralized proximity based services (PBSs). The urban area constraint forces the user mobility to be on the city road network, modeled as a weighted directed graph. The location privacy model exploits location anonymity through subgraph cloaking. Two kinds of location privacy issues have been identified and handled in a unified framework, (i) Subject Anonymity on location updates, i.e., providing location anonymity of the location updater (against the curious PBS provider), and (ii) Object Anonymity on NF querying, i.e., providing location anonymity of friends in NF query responses (against the curious query issuer). In the former, the user simulates the PBS provider's belief (a subgraph) on his location whereabouts, and locally blocks anonymity violating location update requests which is understood by a simulated attack. In the latter, as the NF query processor, the PBS provider simulates the user's mutual beliefs (subgraphs) on friends' location whereabouts obtained through previous NF queries. By a simulated attack, some friends' existence are suppressed from the NF query responses. An experimental evaluation on a real dataset has been conducted. © 2024 ACM.

关键词： Location

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Infodeslib: Python Library for Dynamic Ensemble Learning using Late Fusion of Multimodal Data 4

Infodeslib: Python Library for Dynamic Ensemble Learning usi...

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4th International Workshop on Knowledge-Infused Learning, KiL 2024

作者： Juraev, Firuz El-Sappagh, Shaker Abuhmed, Tamer College of Computing and Informatics Sungkyunkwan University Korea Republic of Faculty of Computer Science and Engineering Galala University Egypt

There has been a notable increase in research focusing on dynamic selection (DS) techniques within the field of ensemble learning. This leads to the development of various techniques for ensembling multiple classifiers for a specific instance or set of instances during the prediction phase. Despite this progress, the design and development of DS approaches with late fusion settings and their explainability remain unexplored. This work proposes an open-source Python library, Infodeslib, to address this gap. The library provides an implementation of several DS techniques, including four dynamic classifier selections and seven dynamic ensemble selection techniques, all of which are integrated with late data fusion settings and novel explainability features. Infodeslib offers flexibility and customization options, making it a versatile tool for various complex applications that require the fusion of multimodal data and various explainability features. Multimodal data, which integrates information from diverse sources or sensor modalities, is a common and essential setting for real-world problems, enhancing the robustness and depth of data analysis. These data can be fused in two main ways: early fusion, where different modalities are combined at the feature level before model training, and late fusion, where each modality is processed separately and the results are combined at the decision level. The library is fully documented following the Read the Docs standards. The documentation, code, and examples are available anonymously on GitHub at https://***/InfoLab-SKKU/infodeslib. © 2024 Copyright for this paper by its authors.

关键词： Python

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Enhanced Lightweight Facial Emotion Recognition Systems for Visually Impaired People 12

Enhanced Lightweight Facial Emotion Recognition Systems for ...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Shehada, Dina Turky, Ayad Rabie, Tamer Hussain, Abir University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah College of Engineering Department of Electrical Engineering Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Science Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350391398

Facial expressions are a vital component of human communication, conveying emotional information that enhances the social experience. However, for individuals with visual impairments, perceiving and interpreting facial expressions can be challenging, hindering their ability to engage fully in social interactions. This paper presents an enhanced facial emotion recognition system specifically designed to aid visually impaired individuals. Two enhanced approaches for facial emotion recognition systems are proposed. The first approach consolidates negative emotions (anger, fear, sadness, disgust) into a single class, while the second approach incorporates diverse training datasets from real-world environments. The negative emotion consolidation approach achieved 90.9% and 94.7% accuracy on the FER2013 and CK+ datasets, respectively. While, the diverse dataset integration approach achieved 84.9% and 70.6% accuracy on FER2013 and CK+ datasets, respectively. This is a significant improvement when benchmarked with other approaches available in the literature. The feasibility of the enhanced proposed systems as assistive technology for the visually impaired indicated its ability to be applied in real-world applications. © 2024 IEEE.

关键词： Assistive technology

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A novel methodology for offline English handwritten character recognition using ELBP-based sequential (CNN)

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Neural computing and Applications 2024年第30期36卷 19139-19156页

作者： Humayun, Muniba Siddiqi, Raheel Uddin, Mueen Kandhro, Irfan Ali Abdelhaq, Maha Alsaqour, Raed Sindh Karachi Pakistan College of Computing and Information Technology University of Doha for Science and Technology 24449 Doha Qatar Department of Computer Science Sindh Madressatul Islam University Sindh Karachi Pakistan Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Technology College of Computing and Informatics Saudi Electronic University Riyadh93499 Saudi Arabia

Handwritten character recognition falls under the domain of image classification, which has been under research for years. But still, specific gaps need to be highlighted as offline handwritten character recognition (OHCR) with the limitation of the unstructured hierarchy of character classification. However, the idea is to make the machine recognize handwritten human characters. The language focused on in this research paper is English, using offline handwritten character recognition for identifying English characters. There are many publicly available datasets, of which EMNIST is the most challenging. The key idea of this research paper is to recommend a deep learning-based ELBP-CNN method to help recognize English characters. This research paper proposes a deep learning CovNet with feature extraction and novel local binary pattern-based approaches, LBP (AND, OR), that is tested and compared with renowned pre-trained models using transfer learning. These parametric settings address multiple issues and are finalized after experimentation. The same hyperparametric settings were used for all the models under test and E-Character, with the same data augmentation settings. The proposed model, named the E-Character recognizer, produced 87.31% accuracy. It was better than most of the tested pre-trained models and other proposed methods by other researchers. This research paper further highlighted some problems, like misclassification due to the similar structure of characters. © The Author(s) 2024.

关键词： Local binary pattern

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Contactless interaction recognition and interactor detection in multi-person scenes

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Frontiers of computer science 2024年第5期18卷 83-95页

作者： Jiacheng LI Ruize HAN Wei FENG Haomin YAN Song WANG College of Intelligence and Computing Tianjin UniversityTianjin 300350China Department of Computer Science and Engineering University of South CarolinaColumbia SC 29208USA

Human interaction recognition is an essential task in video *** current works on human interaction recognition mainly focus on the scenarios only containing the close-contact interactive subjects without other *** this paper,we handle more practical but more challenging scenarios where interactive subjects are contactless and other subjects not involved in the interactions of interest are also present in the *** address this problem,we propose an Interactive Relation Embedding Network(IRE-Net)to simultaneously identify the subjects involved in the interaction and recognize their interaction *** a new problem,we also build a new dataset with annotations and metrics for performance *** results on this datasesthow significant improvements of the proposed method when compared with current methodsdeveloped for human interaction recognition and group activity recognition.

关键词： human-human interaction recognition multiper-son scene contactless interaction human relation modeling

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An Analytical Model for QoS in Mobile Ad Hoc Network using Artificial Neural Network (ANN) 15

An Analytical Model for QoS in Mobile Ad Hoc Network using A...

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15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kumar, Anil Shukla, R.K. Shukla, R.S. Department of Computer Applications Invertis University Bareilly India Department of Applied Science & Humanities Invertis University Bareilly India Department of Computer Science College of Computing and Informatics Saudi Electronic University Saudi Arabia

ISBN: (纸本)9798331300579

This study examines the challenge of predicting end-to-end packet delay in mobile ad hoc networks for Quality of Service (QoS) routing. Factors like node neighbors, interference, and medium access control impact delay unpredictability. We explore the potential of artificial neural networks to enhance accuracy in forecasting these delays, aiming to improve QoS within the dynamic Mobile Ad Hoc Network (MANET) context. We calculated delay using source-destination path length and average neighbors. Two models were built: Regression Neural Networks (RNN) and Radial Basis Function (RBF) networks. Using a network simulator, we gathered data sets for three routing protocols: AODV, DSDV, and DSR. These sets include delay, path length, and average neighbors. RNN outperformed RBF in predicting delay, as determined by various performance metrics. © Grenze Scientific Society, 2024.

关键词： Radial basis function networks

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