Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

“…The proposed methodology aims to: (i) analyze statistical flow and compute entropy, and (ii) implement Machine Learning (ML) algorithms within SDN Intrusion Detection Systems for Internet of Things (IoT) environments. …”
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Orientation Prediction for VR and AR Devices Using Inertial Sensors Based on Kalman-Like Error Compensation by Le Thi Hue Dao, Truong Thanh Nhat Mai, Wook Hong, Sanghyun Park, Hokwon Kim, Joon Goo Lee, Min-Seok Kim, Chul Lee

“…Experimental results demonstrate that the proposed algorithm exhibits higher orientation prediction accuracy compared with conventional algorithms on several open datasets.…”
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Advances in Multi-Source Navigation Data Fusion Processing Methods by Xiaping Ma, Peimin Zhou, Xiaoxing He

“…In recent years, the field of multi-source navigation data fusion has witnessed substantial advancements, propelled by the rapid development of multi-sensor technologies, Artificial Intelligence (AI) algorithms and enhanced computational capabilities. …”
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Maritime decarbonization through machine learning: A critical systematic review of fuel and power prediction models by Son Nguyen, Matthieu Gadel, Ke Wang, Jing Li, Xiaocai Zhang, Siang-Ching Kong, Xiuju Fu, Zheng Qin

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Research on Resource Reservation Strategy for Edge Federation by Hengzhou Ye, Huangran Li, Jiaming Li, Qiu Lu, Gong Chen

“…With the increasing number of users and the continuous expansion of task scales, the resource constraints faced by edge computing are becoming increasingly pronounced. To address these challenges, edge computing has gradually evolved into an edge federation computing model. …”
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Utility-Based Joint Routing, Network Coding, and Power Control for Wireless Ad Hoc Networks by Kaiqian Ou, Yinlong Xu, Xiumin Wang, Wang Liu

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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
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An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

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Analysis of random factors of the self-education process by A. A. Solodov

“…The purpose is to describe observable and unobservable data and developing algorithms for optimal evaluation. Further, such evaluations can be used for the individual characteristics of the process of self-study or for comparison of different students. …”
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Utilizing weak graph for edge consolidation-based efficient enhancement of network robustness by Wei Ding, Zhengdan Wang

“…We compare the proposed algorithm with optimal and approximate algorithms across graphs of varying scales. …”
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Next-Gen Internet of Drones: Federated Learning and Digital Twin Synergy for Energy-Efficient Task Allocation and Seamless Service Migration by Ahmad Arsalan, Tariq Umer, Rana Asif Rehman, Byung-Seo Kim

“…The FD-IoD framework integrates energy harvesting algorithms and optimizes mobility-aware resource management to extend drone lifespan and reduce unnecessary computational overheads. …”
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Privacy-Preserving SGD on Shuffle Model by Lingjie Zhang, Hai Zhang

“…In this paper, we consider an exceptional study of differentially private stochastic gradient descent (SGD) algorithms in the stochastic convex optimization (SCO). …”
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256‐level honey memristor‐based in‐memory neuromorphic system by Harshvardhan Uppaluru, Zoe Templin, Mohammed Rafeeq Khan, Md Omar Faruque, Feng Zhao, Jinhui Wang

“…Experimental results indicate that the inference accuracy of the 256‐level honey memristor‐based neuromorphic system is greater than 88% without cycle‐to‐cycle variations and 87% with cycle‐to‐cycle variations for different optimization algorithms. The overall performance of optimization algorithms with and without variation is compared in terms of energy and latency, where the momentum algorithm consistently outperforms the rest of the algorithms. …”
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Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture by A. V. Kamenskiy, T. M. Akaeva, D. A. Grebenshchikova

“…The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.Conclusions. …”
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Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques by Mohammed Qader Kheder, Aree Ali Mohammed

“…The data, which is collected by sensors and cameras, is processed using various image processing algorithms and it is sent to the cloud to be available for drivers and commuters through a mobile application. …”
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Direction-of-Arrival Estimation for Wideband Chirps via Multi-Line Fitting in the Fractional Fourier Domain by Eulogio G. Huampo, Juliano B. Lima, Jose R. de Oliveira Neto

“…In this context, we also introduce the so-called local discrete SmFrFT, an algorithm for computing partial points of the (discrete) SmFrFT with a further reduction in the number of involved arithmetic operations. …”
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Novel SMA BASED Elmanspiking neural network modelled fuzzy PI controller for speed-torque regulation of PMSM by Lakshmipriya Natarajan, Mamdooh Alwetaishi, Chu Liang Lee, S. D. V. V. S. Bhimeshwar Reddy

“…In this paper, this soft computing controller possess randomness during first phase of weight update and during optimal gain value determination Simulation process for the designed new soft computing controller was done in MATLAB.…”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Therefore, autonomous UAVs have attracted significant research interest, where most of the existing autonomous navigation algorithms suffer from long computation time and unsatisfactory performance. …”
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Research on intelligent routing with VAE-GAN in the internet of body. by Song Qian, Tianping Zhang, Siping Hu

“…Experiments have shown that this scheme can achieve the optimal route according to the transmission capacity of the real-time path and only requires fewer computing resources. …”
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Design and Implementation of a Deep Learning-Based Hand Gesture Recognition System for Rehabilitation Internet-of-Things (RIoT) Environments Using MediaPipe by Nurul Hanis Mohd Dhuzuki, Ahmad Anwar Zainuddin, Nur Anis Sofea Kamarul Zaman, Alin Nur Maisarah Ahmad Razmi, Wonderful Shammah Kaitane, Asmarani Ahmad Puzi, Mohd Naqiuddin Johar, Maslina Yazid, Nor Azlin Mohd Nordin, Shahrul Naim Sidek, Hasan Firdaus Mohd Zaki

“…Several limitations, including latency and distance sensitivity, are addressed in this system with edge computing alongside adaptive algorithms. The key contributions of this research are as follows: First, developing a real-time and cost-effective solution for remote stroke rehabilitation. …”
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