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2023 International conference on Images, Signals, and Computing, ICISC 2023

作者： Litzenberger, Martin Hubner, Michael Kohn, Bernhard Wohlleben, Kilian AIT Austrian Institute of Technology GmbH Giefinggasse 4 Vienna1210 Austria

ISBN: (数字)9781510668171

ISBN: (纸本)9781510668164

Increasing security awareness in the public sector are leading to a more and more widespread use of surveillance applications. Although the available technologies like video processing are already well advanced, they still suffer from high false alarm rates when used under realistic conditions. We present a method for sensor fusion based on probability density maps and a rule engine. The system was tested in a public area using the combination of audio localization, audio classification and video detection using 79 simulated scenarios and 44 hours of sample data recorded over a period of several weeks. The false positive rate decreased by 60% and the event localization rate increased by 25% with the fusion approach compared to the detection performance of individual techniques. © 2023 SPIE.

关键词： sensor data fusion

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Centroiding and Extraction of Tip/Tilt Information from Nonlinear Curvature Wavefront sensor Measurements 9

Centroiding and Extraction of Tip/Tilt Information from Nonl...

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conference on Adaptive Optics systems Ix

作者： Abbott, Caleb G. Crepp, Justin R. Letchev, Stanimir O. Smith, Connor M. Univ Notre Dame Phys & Astron Notre Dame IN 46556 USA Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany

ISBN: (纸本)9781510675186;9781510675179

The nonlinear curvature wavefront sensor (nlCWFS) uses multiple (typically four) out-of-focus images to reconstruct the phase and amplitude of a propagating light beam. Because these images are located between the pupil and focal planes, they contain tip/tilt information. Rather than using a separate sensor to measure image locations, it would be beneficial to extract tip/tilt information directly and routinely as part of the reconstruction process. In the presence of atmospheric turbulence, recovering precise centroid offsets for each out-of-focus image becomes a dynamic process as image structure is altered by changing aberrations. We examine several tip/tilt extraction methods and compare their precision and accuracy using numerical simulations. We find that the nlCWFS outer measurement planes confer more accurate and reliable tip/tilt information than the inner measurement planes, due to their larger geometric lever arm. However, in practice, finite field of view (detector region of interest) effects bias tip/tilt retrieval when using the outer planes due to diffraction. Using knowledge of the z-distance to each plane, we find that applying a best-fit linear model to multiple image centroid locations can offer fast and accurate tip/tilt mode retrieval. For the most demanding applications, a non-linear tip/tilt extraction method that self-consistently uses the speckle field may need to be developed.

关键词： wavefront sensing adaptive optics wavefront reconstruction algorithms

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Uncertainty Assessment of Poses Derived from Automatic Point Cloud Registration in the Context of Stop-and-Go Multi sensor Robotic systems

Uncertainty Assessment of Poses Derived from Automatic Point...

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2024 IEEE International conference on Multisensor Fusion and Integration for Intelligent systems, MFI 2024

作者： Brandstatter, Max Mikschi, Markus Gabela, Jelena Linzer, Finn Neuner, Hans Vienna University of Technology Research Division Engineering Geodesy Department of Geodesy and Geoinformation Vienna1040 Austria

ISBN: (纸本)9798350368031

The poses derived from automatic point cloud registration between stationary laser scans that occur naturally in robotic multi-sensor systems operating in stop-and-go mode have the potential to greatly improve and aid localization and trajectory estimation. The uncertainty assessment of these registered poses is crucial for its correct system integration and utilization, e.g., for mobile mapping applications. However, obtaining ground truth data with sufficient accuracy for both the position and attitude remains challenging. In this paper, we present a novel measurement setup and a data fusion method based on an iterative weighted least squares adjustment to assess the quality of such derived relative poses. The approach is tested and demonstrated in an outdoor experiment covering a driving area of approximately 65 × 7 m. A total station and a laser tracker were used to realize the ground truth. The latter was mounted on a Husky A200 UGV together with a Riegl VZ-600i laser scanner. The realized ground truth enables the determination of the relative poses with respect to a superordinate system with 0.3 mm and 0.04 mrad on average. The relative poses of the automatic registration differ from the reference poses up to a maximum of 3 mm and 0.76 mrad. © 2024 IEEE.

关键词： Information fusion

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VEHIGAN: Generative Adversarial Networks for Adversarially Robust V2x Misbehavior Detection systems 44

VEHIGAN: Generative Adversarial Networks for Adversarially R...

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44th IEEE International conference on Distributed Computing systems (ICDCS)

作者： Shahriar, Md Hasan Ansari, Mohammad Raashid Monteuuist, Jean-Philippe Chen, Cong Petitt, Jonathan Hou, Y. Thomas Lou, Wenjing Virginia Polytech Inst & State Univ Blacksburg VA 24061 USA Qualcomm Technol Inc Boxboro MA USA

ISBN: (纸本)9798350386066;9798350386059

Vehicle-to-Everything (V2x) communication enables vehicles to communicate with other vehicles and roadside infrastructure, enhancing traffic management and improving road safety. However, the open and decentralized nature of V2x networks exposes them to various security threats, necessitating a robust misbehavior detection system (MBDS). While machine learning (ML) has proved effective in different anomaly detection applications, the existing ML-based MBDSs have shown limitations in generalizing due to the dynamic nature of V2x and insufficient and imbalanced training data. Moreover, they are known to be vulnerable to adversarial ML attacks. On the other hand, generative adversarial networks (GAN) possess the potential to mitigate such issues and improve detection performance by synthesizing unseen samples of minority classes and utilizing them during their model training. Therefore, we propose the first application of GAN to design an MBDS. Our contributions are manifold. In the pursuit of an effective GAN-based MBDS, we train and evaluate a diverse set of Wasserstein GAN (WGAN) models and present VEhicular GAN (VEHIGAN), an ensemble of multiple top-performing WGANs, which transcends the limitations of individual models and improves detection performance and adversarial robustness. We present a physics-guided data preprocessing technique that generates effective features for ML-based misbehavior detection. To evaluate the adversarial robustness, we formulate two categories of adversarial attacks against the WGAN-based MBDS. In the evaluation, we leverage the state-of-the-art V2x attack simulation tool VASP to create a comprehensive dataset of V2x messages with diverse misbehaviors. Evaluation results show that in 20 out of 35 misbehaviors, VEHIGAN outperforms the baselines and exhibits comparable detection performance in other scenarios. Particularly, VEHIGAN excels in detecting advanced misbehaviors that manipulate multiple fields in V2x messages simultaneously, r

关键词： vehicular network misbehavior detection systems generative adversarial networks deep learning

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Enhancing Safety in Autonomous Vehicles through advanced AI-Driven Perception and Decision-Making systems 5

Enhancing Safety in Autonomous Vehicles through Advanced AI-...

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5th International conference on Intelligent Data Science Technologies and applications, IDSTA 2024

作者： Alahmed, Yazan Abadla, Reema Al Ansari, Mohammed Jassim Al Ain University Faculty of Engineering Abu Dhabi United Arab Emirates University of Central Lancashire School of Business preston United Kingdom

ISBN: (纸本)9798350354751

Accidents, congested roads, consumption of energy, and emissions may all decrease significantly with the rise of self-driving cars, providing a promising response to social and environmental issues. In this study, researchers investigate the way the integration of innovative AI-driven perception and decision-making systems into AVs impacts safety. AVs have the potential to change transportation by reducing accidents caused mainly by human error. They may operate on their own or in conjunction with human drivers. The primary goal is to investigate and enhance AV safety by creating highly sophisticated perception and decision-making technologies driven by machine learning. Pragmatism research philosophy, experimental research design, and inductive approach serve as the selected methods of the study. In addition, secondary qualitative data analysis methods help evaluate the entire study. The outcomes of the study demonstrated that the advancement of autonomous vehicles depends significantly on the creation of AI-driven sensors. 'Vehicle-to-vehicle (V2x) networks' for communication and safety features increase security, while integrated camera systems with acoustic and thermal sensors improve sensing capacities. Deep learning techniques, especially 'convolutional neural networks (CNN)' and 'fully convolutional networks (FCN)', facilitate accurate object recognition and segmentation. Vehicles' ability to handle difficult road conditions is further improved by a real-time risk evaluation and trajectory planning based on human-like behavioral modeling. © 2024 IEEE.

关键词： advanced driver assistance systems

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Implementation of Improved Energy Balanced Routing Protocol to Enlarge Energy Efficiency in MANET for IoT applications 9

Implementation of Improved Energy Balanced Routing Protocol ...

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9th International conference on advanced Computing and Communication systems, ICACCS 2023

作者： Satyanarayana, P. Bhoomika, K. Mukesh, D. Srujana, P. Bai, R. Manasa Sriramam, Yadavalli S S V. R. Siddhartha Engineering College Department of ECE Vijayawada India S.R.K.R. Engineering College Department of ECE A.P Bhimavaram India

ISBN: (纸本)9798350397376

Mobile Adhoc Networks (MANETs) are mainly composed of minimum power gadgets dispersed over remote locations. Clusters of sensors are arranged. Each cluster identifies a crucial node called a cluster head (CH). To communicate the acquired data to a base station (BS), each CH gathers it from its sensor node. sensors with non-replaceable batteries have been utilized. For MANET, energy consumption is a critical problem. We suggest an improvement strategy to lower energy consumption and improve network lifetime. The energy dissipation during network communications has been reduced by improving the energy balance in clusters across all sensor nodes. A cluster head selection method is the foundation of the enhanced approach. Additionally, an updated TDMA schedule has been put into place. Results from MATLAB 2015a simulations and mathematical analysis demonstrate the feasibility of the suggested strategy. MANET's energy usage has been lowered by about 60%, and the network life cycle has been extended by 73%. © 2023 IEEE.

关键词： Energy utilization

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Coronavirus Disease Outbreak Prediction and Analysis Using Machine Learning and Classical Time Series Forecasting Models

Coronavirus Disease Outbreak Prediction and Analysis Using M...

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2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Rabby, Habibor Rahman Hasan, Mahadi Jahan, Israt Jahan, Rumana Siddiky, Rafiuddin Campbellsville University Department of Computer Science KY United States Washington University of Science and Technology Department of Information Technology VA United States Military Institute of Science and Technology Industrial and Production Engineering Dhaka Bangladesh Technology Wilmington University Department of Information Systems DE United States

ISBN: (纸本)9798331517953

This study explores the efficacy of machine learning and classical time series forecasting models in predicting COVID-19 case counts, addressing a critical global health challenge. We compared four models - Holt-Winters, ARIMA, Facebook Prophet, and xGBoost - across eight countries, forecasting both confirmed and death cases over a 14-day period. Our findings reveal that Facebook Prophet with holiday impact and xGBoost consistently outperform other models in predicting new cases, with xGBoost excelling in forecasting death cases, followed by ARIMA and Facebook Prophet. Notably, xGBoost with a mean absolute error (MAE) of 1.42, mean squared error (MSE) of 4.06, and root mean squared error (RMSE) of 2.01, demonstrated the best performance for death prediction. These results underscore the potential of advanced analytical techniques in pandemic management, offering valuable insights for public health officials and policymakers. By providing accurate short-term projections, these models can facilitate proactive decision-making, resource allocation, and intervention strategies, ultimately contributing to more effective COVID-19 mitigation efforts worldwide. This re- search not only demonstrates the practical application of machine learning in epidemiological forecasting but also highlights the importance of model selection in achieving optimal predictive performance for different aspects of the pandemic. © 2024 IEEE.

关键词： COVID-19

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Simultaneous enhancement of sensitivity, resonant frequency, and overload capability of piezoresistive accelerometers by heavily-doped fillet structures on sensing beams

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IEEE sensors Journal 2025年第11期25卷 19138-19146页

作者： xia, Yong Wang, Tao Lv, Yang Han, xiangguang Yu, Mingzhi Tan, Renjie Huang, Mimi Jia, Chen Zhao, Libo Sun, Lin Yang, Ping Lu, Dejiang Xi'an Jiaotong University School of Mechanical Engineering State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Xi'an710049 China Ningbo CRRC Times Transducer Technology Co. LTD Department of Basic Research and Development Ningbo315021 China Research Institute for Intelligent Sensing Technology and System School of Instrument Science and Technology State Key Laboratory for Manufacturing Systems Engineering State Industry-Education Integration Center for Medical Innovations International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Xi'an Jiaotong University Xi'an710049 China Shandong Laboratory of Advanced Materials and green Manufacturing at Yantai Yantai264000 China

High sensitivity, high natural frequency, and high overload capability are desired for accelerometers used in industrial applications, but simultaneously enhancing all is challenging. Here, via designing novel heavily-doped fillet structures, we prove the sensitivity, resonant frequency, and overload capability can be simultaneously enhanced. The enhancements are attributed to regulations of stress concentration and effective sensing regions by the heavily-doped fillets. The sensors with and without fillets are designed, fabricated, packaged, and tested. The results show a sensitivity of 0.31±0.02 mV/g@5V, a natural frequency of 37.87±2.09 kHz, and an overload of 10040.17±531.76 g for sensors with 10-μm fillets, which are superior to 0.27±0.01 mV/g@5V, 34.13±0.90 kHz, and 7368.55±843.92 g for those no-fillet counterparts. Additionally, the developed sensor further exhibited feasibility in air-bearing vibration monitoring. The proposed design is envisioned to give insights into the novel designs of high-performance stress-based sensors, including accelerometers, pressure sensors, and strain gauges. © 2001-2012 IEEE.

关键词： Strain gages

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On the Impact of Measurements on Location Estimation Using sensors Fusion

On the Impact of Measurements on Location Estimation Using S...

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IEEE SoutheastCon conference on Engineering the Future

作者： Alqudah, Yazan A. Sevil, Hakki Erhan Univ West Florida UWF Dept Elect & Comp Engn Pensacola FL 32514 USA Univ West Florida UWF Dept Intelligent Syst & Robot Pensacola FL 32502 USA

ISBN: (纸本)9798350317107;9798350317114

This paper investigates the impact of measurements availability on the accuracy of position prediction using a mobile device equipped with GPS, acceleration, and gyro sensors. The paper also discusses the effects of the sampling factor for the available data. The experiment results emphasize the importance of sampling factor in achieving robust and reliable location estimation, particularly in challenging environments where GPS signals may be intermittent or compromised. The insights gained from this study may contribute to the advancement of location estimation-based applications, fostering improved autonomous systems in real-world scenarios.

关键词： location estimation sensor fusion sensor measurements

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SLSS-3D A robust 3D hyperchaotic map with coupled transformations 4

SLSS-3D A robust 3D hyperchaotic map with coupled transforma...

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4th International conference on advanced Algorithms and Neural Networks, AANN 2024

作者： Zhang, Yuhao xiong, Lichang Bie, Yuechao School of Artificial Intelligence Wuhan Technology and Business University Wuhan430065 China Institute of Information and Intelligent Engineering Applications China

ISBN: (纸本)9781510686106

Chaotic systems, known for their unique dynamics, are used in cryptography, neural networks, control engineering, and secure communications. However, some classical and improved hyperchaotic systems may have security issues due to insufficient complexity. To address this problem, this study proposes a novel 3D hyperchaotic map named SLSS-3D. The SLSS-3D system derives from classical logistic, sine, and ICMIC maps through nonlinear coupling transformations. It includes two control parameters, α and β, offering a wider range of parameter selection. This enhances resistance to brute-force attacks. This study evaluates the hyperchaotic behavior of the SLSS-3D system through analyses of phase diagrams, bifurcation diagrams, Lyapunov exponent spectra, sample entropy, the 0-1 test, and permutation entropy. The findings reveal that the SLSS-3D system demonstrates superior stability and significant chaotic properties. These characteristics suggest that SLSS-3D has substantial potential for applications in cryptography, artificial intelligence, and secure communications. © 2024 SPIE.

关键词： Secure communication

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