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

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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An anisotropic nonlinear stabilization for finite element approximation of Vlasov-Poisson equations

arXiv

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arXiv 2025年

作者： Wen, Junjie Nazarov, Murtazo Department of Information Technology Division of Scientific Computing Uppsala University Sweden

We introduce a high-order finite element method for approximating the Vlasov-Poisson equations. This approach employs continuous Lagrange polynomials in space and explicit Runge-Kutta schemes for time discretization. To stabilize the numerical oscillations inherent in the scheme, a new anisotropic nonlinear artificial viscosity method is introduced. Numerical results demonstrate that this method achieves optimal convergence order with respect to both the polynomial space and time integration. The method is validated using classic benchmark problems for the Vlasov-Poisson equations, including Landau damping, two-stream instability, and bump-on-tail instability in a two-dimensional phase space. © 2025, CC BY.

关键词： Poisson equation

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LightEnsemble-Guard: An Optimized Ensemble Learning Framework for Securing Resource-Constrained IoT Systems

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IEEE Access 2025年 13卷 101764-101781页

作者： Tanveer, Muhammad Usama Munir, Kashif Amjad, Madiha Alyamani, Hasan J. Bermak, Amine Rehman, Atiq Ur Khwaja Fareed University of Engineering and Information Technology Institute of Information Technology Rahim Yar Khan 64200 Pakistan King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Jeddah 21589 Saudi Arabia Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar

The rapid proliferation of real-time Internet of Things (IoT) devices has increased the need for efficient and accurate security mechanisms. Real-time IoT devices are highly vulnerable to cyberattacks due to their continuous connectivity and limited security mechanisms. In this work, we propose LightEnsemble-Guard, an ensemble learning-based approach specifically designed for resource-constrained IoT environments. Our method achieves a high detection accuracy of 99.55%, with strong precision, recall, and F1-score, while maintaining a low computational cost of just 22.23 seconds. To ensure robustness, we conducted 5-fold cross-validation and ROC curve evaluations, confirming the model’s reliability and generalizability. LightEnsemble-Guard integrates three lightweight classifiers LightGBM, XGBoost, and Extra Trees using a majority voting mechanism to improve detection performance on highly imbalanced datasets without burdening system resources. This ensemble strategy ensures an optimal balance between detection performance and computational resource utilization, making it well-suited for IoT networks, where processing power and memory are limited. The results highlight LightEnsemble-Guard as an effective, scalable and lightweight solution for real-time IoT security, significantly outperforming traditional models in both accuracy and computational efficiency. © 2013 IEEE.

关键词： Attack Detection Cybersecurity Ensemble Learning LightEnsemble-Guard Machine Learning

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Modeling the hallmarks of avascular tumors

arXiv

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arXiv 2024年

作者： Blom, Erik Engblom, Stefan Menz, Gesina Division of Scientific Computing Department of Information Technology Uppsala university Sweden

We present a stochastic computational model of avascular tumors, emphasizing the detailed implementation of the first four so-called hallmarks of cancer: self-sufficiency in growth factors, resistance to growth inhibitors, avoidance of apoptosis, and unlimited growth potential. Our goal is to provide a foundational understanding of the first steps of cancer malignancy while addressing modeling uncertainties, thus bringing us closer to a first-principles grasp of this process. Preliminary numerical simulations illustrate the comprehensiveness of our perspective. © 2024, CC BY.

关键词： Tumors

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A nodal based high order nonlinear stabilization for finite element approximation of Magnetohydrodynamics

arXiv

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arXiv 2024年

作者： Dao, Tuan Anh Nazarov, Murtazo Division of Scientific Computing Department of Information Technology Uppsala University Sweden

We present a novel high-order nodal artificial viscosity approach designed for solving Magnetohydrodynamics (MHD) equations. Unlike conventional methods, our approach eliminates the need for ad hoc parameters. The viscosity is mesh-dependent, yet explicit definition of the mesh size is unnecessary. Our method employs a multimesh strategy: the viscosity coefficient is constructed from a linear polynomial space constructed on the fine mesh, corresponding to the nodal values of the finite element approximation space. The residual of MHD is utilized to introduce high-order viscosity in a localized fashion near shocks and discontinuities. This approach is designed to precisely capture and resolve shocks. Then, high-order Runge-Kutta methods are employed to discretize the temporal domain. Through a comprehensive set of challenging test problems, we validate the robustness and high-order accuracy of our proposed approach for solving MHD equations. © 2024, CC BY.

关键词： Finite element method

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Modeling the Hallmarks of Avascular Tumors

Modeling the Hallmarks of Avascular Tumors

引用

European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2023

作者： Blom, Erik Engblom, Stefan Menz, Gesina Division of Scientific Computing Department of Information Technology Uppsala University Uppsala Sweden

ISBN: (纸本)9783031861727

关键词： Stochastic models

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VISCOUS REGULARIZATION OF THE MHD EQUATIONS

arXiv

引用

arXiv 2024年

作者： Dao, Tuan Anh Lundgren, Lukas Nazarov, Murtazo Division of Scientific Computing Department of Information Technology Uppsala University Sweden

Nonlinear conservation laws such as the system of ideal magnetohydrodynamics (MHD) equations may develop singularities over time. In these situations, viscous regularization is a common approach to regain regularity of the solution. In this paper, we present a new viscous flux to regularize the MHD equations which holds many attractive properties. In particular, we prove that the proposed viscous flux preserves positivity of density and internal energy, satisfies the minimum entropy principle, is consistent with all generalized entropies, and is Galilean and rotationally invariant. We also provide a variation of the viscous flux that conserves angular momentum. To make the analysis more useful for numerical schemes, the divergence of the magnetic field is not assumed to be zero. Using continuous finite elements, we show several numerical experiments including contact waves and magnetic *** Codes 34A45 © 2024, CC BY.

关键词： Magnetohydrodynamics

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Evaluating the Optimal Self-Checking Carry Propagate Adder for Cryptographic Processor 15

Evaluating the Optimal Self-Checking Carry Propagate Adder f...

引用

15th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2022

作者： Akbar, Muhammad Ali Wang, Bo Bermak, Amine College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar

ISBN: (纸本)9781665464994

With the increasing number of invasive attacks, cryptographic processors are becoming more susceptible to failure. Therefore, the desire for reliable hardware is becoming increasingly important. Since an adder is a vital component in the hardware design of cryptographic protocols, a reliable adder can significantly improve the vulnerability against invasive attacks. Adders with different architectures have already been widely studied and analyzed and appropriate types have been proposed based on the application. This paper considers the design of adder most suitable for reliable cryptographic operation and investigates the optimal self-checking carry propagate adder design offering the best possible performance in terms of latency, delay, and area. In terms of area versus delay, the self-checking parallel ripple carry adder (PRCA) with 23.4% area overhead as compared to the self-checking ripple carry adder (RCA) provides a delay efficiency of 70.31%. However, the area-delay product for 64-bit self-checking designs showed that the hybrid adder is 71.2%, 21.4%, and 37.9% more efficient than the RCA, PRCA and carry look-ahead adder design, respectively. © 2022 IEEE.

关键词： Adders

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The impact of language on students emotional states in educational games: A comparative study 35

The impact of language on students emotional states in educa...

引用

35th British HCI Conference Towards a Human-Centred Digital Society, HCI 2022

作者： Assaf, Duha Awni Al-Thani, Dena Banire, Bilikis Information and Computing Technology Division College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

Capturing students emotions while playing an educational game is one approach to assess their motivation towards learning. The language of educational games could serve as a motivating factor for players. This study compares two languages (Arabic and English) in an educational game to understand and compare the effect of the two languages on learning motivation via emotions. An experimental study was conducted with 30 Arabic-speaking students (Male n=13, Female n= 17) while playing an educational game in both Arabic and English languages, and their emotions were recorded. The result shows that participants express significant negative emotions (anger [p 0.05], contempt [p 0.05], and sadness [p 0.05]) while playing the Arabic version of the game than the English version. indicating that participants preferred the English version. These findings suggest that emotion might help evaluate language preference in educational games development. © 2022 *** Rights Reserved.

关键词： Students

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Smart Diaper Embedded with Fully Printed Sensors for Wireless Healthcare and Monitoring 5

Smart Diaper Embedded with Fully Printed Sensors for Wireles...

引用

5th IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Ali, Shawkat Khan, Arshad Bermak, Amine College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9781665457330

In this research, a real-time healthcare and monitoring wireless system is developed to monitor vital signs of a wearer i.e., temperature, respiration rate, and wetting volume on a smartphone. The smart diaper consists of two main units, a detachable electronic module and a disposable printed biosensors patch deployed on a commercial diaper. Custom sensors array was designed and fabricated in a single patch through printed electronics technology by using biocompatible materials on a thermal transfer substrate. The sensors patch was designed in such a way to accurately collect the vital signs data by placing each sensor at appropriate site. Individual sensors were characterized for their electrical and mechanical properties. The overall system was tested, and data was wirelessly transmitted to a smartphone via Bluetooth. The main purpose of the proposed smart diaper is to minimize the effort of caregiver and avoid infection, rashes, and discomfort. We believe this work will open a new window for the printed electronics systems for special needs, elderly, and infant healthcare. © 2023 IEEE.

关键词： Wetting

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