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Baker’s Map based Chaotic image Encryption in Military Surveillance systems 1

引用

international conference on internet of Everything and Quantum Information Processing, IEQIP 2023

作者： Rajendiran, Nithya Paranthaman Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur India

ISBN: (数字)9783031619298

ISBN: (纸本)9783031619281

One of the primary problems in military surveillance systems is the safety of the visual data gathered by the sensor nodes installed in the different areas of the Visual sensor network and the remotely operated devices. There are several cryptographic algorithms available to secure the visual information. Several chaotic schemes worked well because they were more resistant to threats and had greater entropy levels. But, it takes a lot of time to finish the encryption step. Traditional approaches had the drawback that increasing encryption strength slowed calculation speed. This paper presents a scheme called "baker’s map chaotic method based image encryption" to accelerate the encryption process in a network of visual sensors without weakening the encryption method. The findings indicate that the system’s functionality is improved when the computation time is reduced to sixty seconds and the PSNR is increased to 15 dB. The performance of the chaotic method is compared by using key space analysis, key sensitivity analysis, correlation coefficient analysis, noise analysis, Entropy analysis, and Speed analysis. The IBM SPSS statistical tool was also used to do statistical analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Sensitivity analysis

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20th Chinese Intelligent systems conference, CISC 2024

20th Chinese Intelligent Systems Conference, CISC 2024

引用

20th Chinese Intelligent systems conference, CISC 2024

ISBN: (纸本)9789819786497

The proceedings contain 202 papers. The special focus in this conference is on Chinese Intelligent systems. The topics include: Modeling of Interval Type-2 Fuzzy Logic System by Semi-tensor Product;Robust Adaptive Control of Missiles based on Fuzzy RBF Neural Network;deep Reinforcement Learning of Physically Simulated Character Control;the Game of Degree of Target-Attacker-Defender Game With Non-zero Capture Radius;Visual Inertial 3D Reconstruction System based on KLT Optical Flow and Voxel Hash;analysis of Students’ Class Status based on Deep Learning;fault-Tolerant Attitude Control of Hypersonic Flight Vehicles based on Extended Adaptive Iterative Learning;predefined-Time Control of Robot systems with Prescribed Performance Guarantees;dynamic Coverage of Unicycle Robots with Anisotropic Sensing for Time-Priority;method for Evaluating the Multi-factor Decision-Making Efficiency based on Dynamic Bayesian Network;submarine Cable Target Search based on Improved Biological Neural Network;end-to-End mmWave-based Human Pose Estimation from Raw signal;urban Sewage Treatment Plant Simulation System based on Industrial internet;Load Matching Design and Multi-objective Optimization of Helicopter EHA;Testability Design and Verification of Typical Functional Links of CNI System;adaptive Sliding Mode Tracking Control for Multiple High-Speed Trains with Actuator Saturation and Parameter Uncertainties;Abnormal Data Detection based on Dual-Factor Weighted SVDD for Multimode Batch Processes;dual-Branch Attention Dense Residual Network based on Negative image for image Denoising;Research on Testability Work Planning technology for Aviation Equipment based on DoDAF;aero Engine Instability Prediction and Detection Method based on Gated Recurrent Neural Networks;Seven-Degrees-of-Freedom Robotic Arm Path Planning based on Improved RRT;dynamic Event-Triggered based Coherent Formation Control for Multi-robot systems;adaptive Prescribed Time Prescribed Performance Control for High-Order No

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20th Chinese Intelligent systems conference, CISC 2024

20th Chinese Intelligent Systems Conference, CISC 2024

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20th Chinese Intelligent systems conference, CISC 2024

ISBN: (纸本)9789819786534

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20th Chinese Intelligent systems conference, CISC 2024

20th Chinese Intelligent Systems Conference, CISC 2024

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20th Chinese Intelligent systems conference, CISC 2024

ISBN: (纸本)9789819786572

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Velocity and Distance Estimation of Multiple Objects Using YOLO-based OFDM Radar System 15

Velocity and Distance Estimation of Multiple Objects Using Y...

引用

15th international conference on Information and Communication technology Convergence, ICTC 2024

作者： Jeon, So-Yeon Hyun, In-Young Jeong, Eui-Rim Hanbat National University Dept. of Artificial Intelligence Daejeon Korea Republic of Hanbat National University Dept. of Artificial Intelligence Software Daejeon Korea Republic of

ISBN: (纸本)9798350364637

In this study, we propose a method for simultaneously estimating the speed and distance of multiple objects using a YOLO model within an OFDM radar system. The proposed technique inputs a 2D spectrogram image generated from OFDM radar signal processing into the YOLO model to predict the speed and distance of objects. Simulation results demonstrate that the proposed method performs well in recognizing multiple objects. Notably, the speed and distance estimation accuracy improves as the number of OFDM symbols increases and the number of objects decreases. The proposed technology is applicable not only to 5G but also to 6G OFDM signals. © 2024 IEEE.

关键词： 5G mobile communication systems

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Performance Evaluation of Micro-Doppler based UAV Identification Using Different 5G Frame Structures 2

Performance Evaluation of Micro-Doppler Based UAV Identifica...

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2nd international conference on Mobile internet, Cloud Computing and Information Security (MICCIS)

作者： Ma, Dingyou Wei, Jiachen Zhang, Qixun Wei, Zhiqing Jiang, Weiwei Guo, Ningyan Huang, Sai Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing Peoples R China

ISBN: (纸本)9798350389913;9798350389906

The integrated sensing and communication (ISAC) technology is considered as a key feature in the upcoming B5G/6G networks. Currently, most ISAC research focuses on target detection and localization, with limited attention given to target identification. The lack of focus on target identification results in challenges in distinguishing small unmanned aerial vehicles (UAVs) from other birds or insects in urban low-altitude scenarios. In this study, we propose a method for extracting micro-motion feature spectrograms of UAVs using 5G signals. Unlike traditional radar systems, ISAC base stations utilize communication waveforms and time-division duplex (TDD) types with downlink and uplink slots for environmental sensing. To assess the performance of UAV identification using different TDD types, we evaluate the mean squared error in estimating rotor blade parameters for each TDD type. Simulation results demonstrate the feasibility of utilizing 5G signals to extract micro-motion features of UAVs. While all evaluated 5G TDD types show promising results in recovering rotor UAV blade parameters at high signal-to-noise ratios (SNRs), their estimation performance varies significantly at low SNRs. These findings provide a solid foundation for future research on micro-Doppler recognition in ISAC systems.

关键词： integrated sensing and communication micro-Doppler signature micro-motion parameters extraction

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FKAN-GMFNet: Fourier Kolmogorov-Arnold-based Group Multi-scale Fusion Network for Aneurysm image Segmentation

FKAN-GMFNet: Fourier Kolmogorov-Arnold-based Group Multi-sca...

引用

2025 IEEE international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Pang, Shanchen Zhao, Xue Zhang, Yulin Zhao, Yawu Ding, Hengtao Zhao, Zhiyuan Qiao, Sibo Qingdao266580 China College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao266590 China The College of Software Tiangong University Tianjin300387 China

ISBN: (纸本)9798350368741

KAN-based networks, while offering improved interpretability compared to traditional models used in medical image segmentation, often struggle with limited adaptability to diverse imaging environments, making them less ideal for such tasks. To address this issue, we propose a Fourier Kolmogorov-Arnold-based (FKAN) Group Multi-scale Fusion Network, termed FKAN-GMFNet, which incorporates an FKAN layer into a labeled intermediate representation, introducing an Enhanced-FKAN block. Furthermore, we develop the Attention Group Multi-scale Aggregation (ATGMA) module, which leverages attention mechanisms and grouping strategies to effectively fuse feature masks with both high- and low-scale feature information, thereby achieving a comprehensive multi-scale feature representation. Extensive experiments demonstrate that the FKAN-GMFNet significantly outperforms seven state-of-the-art methods in both Dice and IoU scores, where the Dice and IoU scores for the IAS-L dataset are 88.82% and 80.09%, respectively. Code is available at https://***/zx123868/FKAN-GMFNet. © 2025 IEEE.

关键词： Fourier Kolmogorov-Arnold Intracranial aneurysms Medical image Segmentation

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Optimization of Passivity-based Controller for a Hybrid Vehicle Power Source using the Gray Wolf Algorithm 8

Optimization of Passivity-Based Controller for a Hybrid Vehi...

引用

8th IEEE international conference on image and signal Processing and their Applications, ISPA 2024

作者： Bedda, Said Kraa, Okba Mohammedi, Messaoud Zabia, Djallal Eddine Tegani, Ilyes Benbraika, Mohamed Kamel Mohamed Khider University Energy Systems Modeling Laboratory Biskra Algeria Mohamed Khider University LI3CUB Laboratory Biskra Algeria University Center of Barika Department of Science and Technology Barika Algeria University of El-Oued El-Oued Algeria

ISBN: (纸本)9798350309249

This paper introduces an enhanced approach for the control of hybrid sources, specifically fuel cells and batteries, within a hybrid electric vehicle. The proposed enhancement involves integrating the Gray Wolf Optimization algorithm with the passive-based control technique. The primary aim of this research is to enhance the operational characteristics of the studied system that is governed by the passivity-based control approach. This enhancement is achieved by optimizing the damping matrix parameter using the Gray Wolf Optimization algorithm. It is noteworthy that prior studies utilizing this technique did not address its impact, considering it a stochastic value ranging from 0 to 1. The central focus remains on proficiently and effectively managing the energy exchange between the two sources. Through Simulink-Matlab simulations, the outcomes underscore the influence of the damping matrix parameter on the overall dynamic performance of the system. Moreover, these results emphasize its pivotal role in achieving tracking precision and system robustness. This research constitutes a significant advancement in the realm of sophisticated control methodologies for hybrid power sources. Furthermore, it lays the groundwork for future investigations and the potential implementation of supplementary energy management strategies based on this innovative technique. © 2024 IEEE.

关键词： Optimization

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Research on Optimization Algorithm of Abnormal Driving Behavior Detection based on PFLD

Research on Optimization Algorithm of Abnormal Driving Behav...

引用

2023 international conference on image, signal Processing, and Pattern Recognition, ISPP 2023

作者： He, Jing Dong, Chen Di, YuTing An, JiaHeng Gao, JiaXing Liu, ZhiJiang School of Computer Science and Engineering Tianjin University of Technology Tianjin China

ISBN: (纸本)9781510666351

Driver's fatigue driving and mood are two important factors that cause traffic accidents, and with the widespread use of mobile devices, it is of significant research value to detect driver's abnormal driving behavior on the mobile terminal. In this paper, the PFLD model is used on mobile to obtain face keypoints and improve the EAR by fusing binocular opening and closing degree to detect abnormal driving behavior such as fatigue and mood. Fatigue detection integrates the improved EAR, yawning duration, head pitch angle and other multiple features to determine, which mainly includes the process of extracting the driver's both eyes and mouth features through the PFLD model, monitoring the driver's heart rate and head distance with internet of Things devices, constructing feature vectors and using SVM to determine driving fatigue. The threshold parameters are selected by calculating the five-dimensional features of the face, and the driver's mood is detected based on KNN. Through experiments, the driver fatigue detection accuracy is about 90% and the mood recognition accuracy is up to 96%. © 2023 SPIE.

关键词： Feature extraction

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A Fault Diagnosis Method of GIS High Voltage Isolation Switch based on FA-SVM 5

A Fault Diagnosis Method of GIS High Voltage Isolation Switc...

引用

5th international conference on Smart Power and internet Energy systems, SPIES 2023

作者： Yue, Yiqiao Lu, Senxiang Wang, Yibing Zhang, Bowen School of Information Science and Engineering Northeastern University Shen Yang China

ISBN: (纸本)9798350371741

GIS high voltage isolation switch is an important equipment in power grid operation. In order to avoid the safety and economic loss caused by the fault of high voltage isolation switch, a fault diagnosis method of GIS isolation switch based on FA-SVM is proposed in this paper. Firstly, the feature extraction of voltage, current and Angle signal of the control motor is carried out and the model is trained. Then the fault diagnosis was carried out by FA-SVM model. The experimental results show that this method can effectively identify two common faults of stuck and loosened card. © 2023 IEEE.

关键词： Failure analysis

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