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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Tripathi, Padmaja Chandra, Harish Ramkeval Madan Mohan Malviya University of Technology Department of Mathematics and Scientific Computing Gorakhpur273010 India MJP Rohilkhand University Department of Applied Mathematics Bareilly India

ISBN: (纸本)9798350368109

Diseases caused by parasites proliferate quickly over the globe. As a result, their control intervention needs to be swift and comprehensive. Preventing chronic diseases can be accomplished by using multi-modal communication to attract attention and enhance awareness. This study presents a nonlinear dynamical model to evaluate the impact of media knowledge on the dissemination of illnesses carried by vectors. In this research, we propose a network model for wide-area multi-media communication. Positiveness, simple reproduction number equilibria, numerical simulation, and a fitted model using Delhi malaria data are used to analyze the mathematical model. An informed community makes it more difficult for disease to spread. Constant multi-media efforts combined with quick communication can effectively eradicate the illness. © 2024 IEEE.

关键词： Malaria network model social media stability

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Autism Spectrum Disorder Detection Via Eye Gaze Analysis 2

Autism Spectrum Disorder Detection Via Eye Gaze Analysis

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Das, Sujay Chotia, Akshat Maheswari, K. M. Uma Sadiq, A.K. SRM Institute Of Science & Technology Department Of Computer Science & Engineering Chennai India University of Technology and Applied Sciences College of Computing and Information Science Suhar campus Oman

ISBN: (纸本)9798350365269

Autism is a complex neuro - developmental condition characterized by challenges in social interaction and communication. Early diagnosis and intervention are crucial for effective support. This paper presents a novel approach for autism detection leveraging Convolutional Neural Networks (CNNs) to analyze eye gaze patterns. The proposed method aims to provide an objective and efficient tool for the early screening of Autism. We begin by collecting eye gaze data from a diverse sample of individuals, including both Autism -diagnosed and non Autism individuals. The dataset is preprocessed to extract relevant features from the eye gaze sequences, capturing subtle but significant differences in gaze patterns between the two groups. A CNN architecture is designed and trained on this preprocessed dataset. The network is optimized to automatically learn discriminative features that distinguish between Autism and non Autism gaze patterns. Transfer learning techniques mobilenetv2 are employed to further enhance model performance. The trained CNN demonstrates promising results in accurately classifying individuals into Autism and neurotypical categories. Comprehensive evaluation metrics, including accuracy and loss, attest to the model's effectiveness. © 2024 IEEE.

关键词： Convolutional neural networks

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An Enhancement of Object Detection Using YOLO V8 and Mobile Net in Challenging Conditions

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SN Computer Science 2025年第4期6卷 1-20页

作者： Pasupuleti, Shailaja Ramalakshmi, K. Gunasekaran, Hemalatha Arokiaraj, Rex Macedo Debnath, Saswati Jebaseeli, T. Jemima Department of Computer Science and Engineering Alliance University Karnataka Anekal Bangalore India AU-Centre of Excellence Department of Computer Vision Alliance University Karnataka Anekal Bangalore India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Computer Science and Engineering Alliance University Karnataka Bangalore India Division of Artificial Intelligence and Machine Learning Karunya Institute of Technology and Sciences Coimbatore India

Autonomous drones and deep learning neural networks are becoming popular tools to revolutionize aircraft operations by partially automating visual inspection processes in aircraft maintenance. The research aims to provide a trustworthy method for locating and classifying surface flaws on aircraft, such as dents, fractures, corrosion, and a few other anomalies. To assess the model performance with and without a lightweight network integration, the implementation merges YOLOv8 and Mobile Net architectures, using dropout regularization and data augmentation approaches. To guarantee the model's performance in low-light situations, the dataset has been carefully selected to contain images replicating such settings. Annotation, environment setup, model training, and online dataset scraping are all covered by the thorough technique. A web-scraped dataset is used to train and validate two popular semantic segmentation algorithms, YOLOv8 and Mobile Net, which show enough performance for segmenting and grading aircraft surface problems in practical settings. The results show that precision and recall values are improved using a hybrid technique that ensembles trained Mobile Net and YOLOv8 models. Using COCO metrics, in the proposed approach an assessment of Ensemble WBF, Mobile Net-YOLO, and YOLOv8 outcomes on test and validation sets, guaranteed reliable object recognition and classification abilities. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Aircraft Classification Mobile-Net Object detection Weighted Box Fusion YOLOv8

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A Methodical Framework for Conducting Reconnaissance and Enumeration in the Ethical Hacking Lifecycle 22

A Methodical Framework for Conducting Reconnaissance and Enu...

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22nd European Conference on Cyber Warfare and Security, ECCWS 2023

作者： Barman, Fouz Alkaabi, Nora Almenhali, Hamda Alshedi, Mahra Ikuesan, Richard Computing and Applied Technology Department College of Technological Innovation Zayed University Abu Dhabi United Arab Emirates

ISBN: (纸本)9781914587702

Reconnaissance and enumeration are both equally significant phases of the penetration testing lifecycle. In hindsight, both reconnaissance and enumeration seem to be very similar as the pair involve information gathering. Whilst reconnaissance leverages passive approaches without direct interaction with the target, enumeration exploits susceptibilities and vulnerabilities in direct client-server communication. Both phases involve gathering information and pinpointing the attack surface within the network of the target. To do so, powerful tools such as Nmap and Netcat are utilized by ethical hackers and penetration testers to identify and resolve security vulnerabilities and weaknesses. Nmap is an open-source command-line tool used for information gathering, network discovery, and security auditing. Whereas Netcat is a back-end tool that manages networks, monitors traffic flow between systems, as well as allows port scanning and listening. However, the plethora of tools and approaches available for these two phases often introduce inconsistencies and time wastage, which can lead to frustration and poor outcome for inexperienced penetration testers. Additionally, not all commands found online are relevant and applicable. In such situations, there is a high probability that the user will feel overwhelmed and exasperated with the overflow of new and foreign information. To address this daunting challenge, this study developed a methodical framework that can provide a technical guide for the reconnaissance and enumeration phases of the penetration testing lifecycle. Furthermore, a clear and thorough step-by-step procedure and detailed explanations of each stage and commands initiated using Nmap and Netcat are provided. The output of this study will be extremely beneficial and informative to a vast group of audience, ranging from university students majoring in security to individuals interested in ethical hacking, and even someone looking for a job with a position of a p

关键词： Personal computing

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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Solving 2 by 2 Grid Sudoku Problem using Grover's Algorithm with Intel Quantum SDK 13

Solving 2 by 2 Grid Sudoku Problem using Grover's Algorithm ...

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13th International Conference on Advanced Computer Information Technologies, ACIT 2023

作者： Shinde, Tejas Gambo, Yaknan John Rasch, Kevin Liebelt, Helena Li, Rui Deggendorf Institute of Technology High Performance Computing and Quantum Computing Deggendorf Germany Quantum Computing Research Intel Inc HillsboroOR United States Deggendorf Institute of Technology Department of Applied Computer Science Deggendorf Germany

Quantum technologies are moving towards enabling real world uses and as these technologies develop. The most important thing that differs Quantum from classical computers is that Quantum Computers can do 'multiple' tasks at the same time as opposed to the classical computers doing a single task at a time. This phenomenon has led to the discovery of a few algorithms that are faster than regular computers. One such algorithm is the Grover's Algorithm[l]. This algorithm has shown a few real-world applications such as Quantum Search Algorithm, Travelling salesman, etc[2]. In this paper, Grover's algorithm is introduced, and a 2 x 2 Sudoku example is solved using Intel Quantum Software Development Kit[3]. The Intel Quantum SDK is quite new and in this paper we show how a simple Grover's Problem can be implemented in the SDK. Sudoku is a popular number-based puzzle game played on a grid consisting of nine squares subdivided into smaller 3x3 grids. The objective is to fill the grid with numbers from 1 to 9, ensuring that each row, column, and 3x3 grid contains all numbers exactly once. © 2023 IEEE.

关键词： Qubits

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Digital forensic in a virtual world: A case of metaverse and vr 22

Digital forensic in a virtual world: A case of metaverse and...

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22nd European Conference on Cyber Warfare and Security, ECCWS 2023

作者： Ali, Tayba Al Alfulaiti, Sara Abuzour, Manal Almaqahami, Sheikha Ikuesan, Richard Computing and Applied Technology Department College of Technological Innovation Zayed University Abu Dhabi United Arab Emirates

ISBN: (纸本)9781914587702

Metaverse is a virtual space where users can interact with each other. It is a combination of virtual reality, augmented reality, and mixed reality. This evolving technology can offer many exciting opportunities that can be used for individuals and businesses. Although this technology has many advantages, people are misusing it for their benefit. Many cyberattacks are occurring in the metaverse world because it has various vulnerabilities and privacy issues. This paper explains four cyberattacks and a case scenario of each attack as it relates to the metaverse. Additionally, this study developed a metaverse forensic framework that can be used to investigate cyberattacks in the metaverse world. Furthermore, this study describes how forensic examiners can conduct a forensic investigation using state-of-The-Art forensic solutions and tools. The developed framework can be used by forensic examiners, security researchers, as well as the general scientific community for the security of the metaverse. © 2023 Curran Associates Inc.. All rights reserved.

关键词： Mixed reality

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Empowering Breast Cancer Detection with AI: A Modified Support Vector Machine Approach for Improved Classification Accuracy 4

Empowering Breast Cancer Detection with AI: A Modified Suppo...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Palarimath, Suresh Maran, Pyingkodi Thenmozhi, K. Shiny, K.V. Sujatha, T. N.r, Wilfred Blessing College of Computing and Information Sciences University of Technology and Applied Information Technology Department Sciences Salalah Oman Kongu Engineering College Department of Computer Applications Erode India Department of Compute Science Bengaluru India Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Chennai India Sri Krishna College of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India College of Computing and Information Sciences Univesity of Technology and Applied Sciences Information Technology Department Ibri Oman

ISBN: (纸本)9798350385793

Breast cancer poses a significant threat to women's health, being a leading cause of cancer-related mortality among female population. In recent years, machine learning has emerged as a promising approach in medical field, particularly in detection and classification tasks. However, existing algorithms often exhibit suboptimal accuracy, necessitating improved methodologies. This research presents a novel approach using a Modified Support Vector Machine (MSVM) for breast cancer classification into benign and malignant categories. Leveraging the Wisconsin Breast Cancer Dataset (WBCD), preprocessing techniques are applied to enhance data quality. Principle Component Analysis (PCA) reduces dimensionality, while linear Discriminant Analysis (LDA) extracts discriminative features crucial for classification. The proposed MSVM classifier achieves exceptional performance, with a classification accuracy of 99.42%, outperforming other existing methods such as Deep Convolutional Neural Networks and Fuzzy Rule-based Systems. These results highlight the efficacy of the MSVM approach in accurately distinguishing between benign and malignant breast cancer cases, showcasing its potential as a reliable tool for medical image analysis and cancer diagnosis. © 2024 IEEE.

关键词： Convolutional neural networks

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A lightweight identity based generalized signcryption scheme for secure communication in standard model

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International Journal of Information technology (Singapore) 2024年第2期16卷 1221-1229页

作者： Singh, Tej Kumar, Mukesh Gelmecha, Demissie Jabir Thakur, Ganesh Kumar Tyagi, Vikas Sori, Worku Jifara Department of Applied Sciences ABES Engineering College UP Ghaziabad India Institute of Applied Sciences & Humanities GLA University UP Mathura India Department of Electronics and Communication Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia Department of CSE IMS Engineering College UP Ghaziabad India Department of Computer Science School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia

The implementation of secure communication in the Industrial Internet of Things (IIoT) has made and it is a significant security concern. Identity-based generalized signcryption scheme is one among the cryptographic tools available that offers a secure way out to meet the security needs of IIoT. Our proposal is a lightweight scheme, an efficient identity-based generalized signcryption that works as an encryption signature, or signcryption scheme using only one algorithm in a standard model. This scheme is appropriate for storage-limited environments like wireless sensor networks and smart cards due to its lightweight nature. This means that it can be implemented in a range of IIoT applications where resources are limited, without compromising on security or efficiency. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Bilinear Pairing Generalized signcryption Identity-based cryptography Signcryption

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Performance Analysis of Routing Protocols in VANETs using OSM, SUMO, and NS2 2

Performance Analysis of Routing Protocols in VANETs using OS...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Thangam, S. Aaditi Avvaru, Ananya Tandon, Aryan Kumari, J. Jesy Janet Saleem Raja, A. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science & Engineering Bengaluru India University of Technology and Applied Sciences-Shinas Oman

ISBN: (纸本)9798350360523

With growing urbanization there is a need to manage vehicle-to-vehicle communication for intelligent communication in congested traffic. The performance of the widely used routing protocols AODV, DSDV, DSR, LAR, and ZRP is examined in this research in relation to traffic circumstances on a particular highway. Utilizing OSM data, integrated with NS2 and SUMO, realistic traffic scenarios are simulated. ZRP is a hybrid protocol that handles local communication within zones and LAR bridges the gap between the nodes and zones. This increases communication efficiency. Simulation of scenarios gives a clearer idea of how the dissemination is happening and helps in performance analysis. The protocols are assessed using important performance criteria in this study by means of a methodical approach that includes data collecting, simulation, and execution. Comparison of the metrics for the protocols helps in protocol selection for given scenarios, optimization, and standardized evaluation. The specific metrics considered for performance evaluation include Packet Delivery Ratio, Average End-to-End Delay, Average Throughput, Packet Drop Rate, and Normalized Routing Load. © 2024 IEEE.

关键词： Routing protocols

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