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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications"

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Design and Analysis of Hybrid Inset Feed and Probe Feed Microstrip Patch Antenna Array for Sub-6GHz applications 7

Design and Analysis of Hybrid Inset Feed and Probe Feed Micr...

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7th IEEE conference on Information and Communication Technology, CICT 2023

作者： Gupta, Aditya Singh, Amit K. Jharia, Bhavna Jabalpur Engineering College Department of Electronics and Communication Engineering Jabalpur India Indian Institute of Technology Patna Department of Electrical Engineering Patna India

ISBN: (纸本)9798350305173

This research work presents the design and comparative analysis of the performance of a hybrid feed 64 elements low-profile rectangular microstrip patch antenna (RMPA) array on a low-cost FR-4 substrate of thickness 1.6mm to achieve high gain and directivity at 3.5 GHz frequency. At Sub-6 GHz band a single RMPA, 2×2, 4×4, and 8×8 array is designed, and a T-junction equal power splitting power divider is used to feed the array network. The overall size of the proposed 8×8 array is 550×550×1.6mm3 and it achieves the highest gain among all also achieves a directivity of 25.01 dBi, outperforming 2×2, 4×4 arrays, and an RMPA. The hybrid feeding mechanism, which includes inset feeding and probe feeding was found to achieve a wider bandwidth and a more uniform radiation pattern, making it a promising option for advanced antenna arrays. On analyzing the proposed arrays in terms of reflection coefficient, VSWR, gain, directivity, and radiation patterns, it was found that the gain and directivity increased and side lobe levels (SLL) decreased with the increasing number of elements in the array. This study's results can guide the design and optimization of RMPAs for various applications in wireless communication systems such as satellite communication, wireless sensor networks, and radar systems. © 2023 IEEE.

关键词： Feeding

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SwarmCatcher: An AI-Powered Anti-Drone Surveillance System for Public Safety Over 5G and Beyond Ecosystems 28

SwarmCatcher: An AI-Powered Anti-Drone Surveillance System f...

引用

28th conference on Innovation in Clouds, Internet and Networks, ICIN 2025

作者： Kalafatidis, Sarantis Tsiktsiris, Dimitrios Trakos, Dimitrios Lalas, Antonios Votis, Konstantinos Tzovaras, Dimitrios Centre for Research and Technology Hellas Information Technologies Institute Greece

ISBN: (纸本)9798331542399

The proliferation of unmanned aerial vehicles (UAVs) presents significant challenges to public safety and critical infrastructure protection. This paper introduces SwarmCatcher, an innovative AI-powered anti-drone and surveillance system designed to detect and classify UAV threats in real-time. SwarmCatcher integrates multi-sensor technologies, including optical, thermal, RF, and acoustic systems, with advanced AI algorithms to provide thorough situational awareness. Utilizing the low-latency, high-throughput capabilities of cloud-native architecture and 5G networks, the system supports scalable deployment across diverse environments, offering rapid threat mitigation. Real trials were conducted, utilizing 5G infrastructures in the FIDAL and CERTH testbeds, evaluating and demonstrating SwarmCatcher’s potential to address the requirements of public safety agencies and pave the way for integration with 6G networks. The paper investigates SwarmCatcher’s architecture, key performance metrics, and its role in advancing next-generation vertical-specific applications for public safety. © 2025 IEEE.

关键词： 5G mobile communication systems

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Image classification through scattering media using Optronic convolutional neural networks

Image classification through scattering media using Optronic...

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2022 conference on Infrared, Millimeter, Terahertz Waves and applications, IMT 2022

作者： Huang, Zicheng Gu, Ziyu Gao, Yesheng State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781510662476

Object classification behind a complex inhomogenous medium remains a significant challenge in many fields. Valid information is hardly extracted from speckles owing to the distortion of scattering media. Recent years deep learning has shown powerful capability in classifying object from scattered speckle patterns. However, large-scale computations and pure digital procedures set a challenging task for deep neural networks running in optics. Here, we present an optronic technique for object classification through random diffuser media. A group of fourier lens and a programmable spatial light modulator, form an optronic convolutional neural networks(OPCNN) with optimized kernels. The CMOS camera not only works as an image detection sensor but a non-linear activation layer by the curve built-in. We demonstrated the technique classification result using the airy disk intensity of every candidate channel. The trained OPCNN shows high-quality object predictions on the speckle patterns. Our work paves the way to an all-optical approach for imaging through scattering media. © 2023 SPIE.

关键词： Convolution

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2022 International conference on Electromagnetics in advanced applications, ICEAA 2022

2022 International Conference on Electromagnetics in Advance...

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23rd International conference on Electromagnetics in advanced applications, ICEAA 2022

ISBN: (纸本)9781665481113

The proceedings contain 145 papers. The topics discussed include: efficient broadband modeling of microwave devices with machine learning and analytical extension of eigenvalues;influence of antenna systems with metamaterial screens composition and geometric parameters on mutual coupling between antennas;wave-particle interactions in earth outer radiation zone;phaseless bi-spherical near-field measurement;spherical near field to far field transformation algorithm for offset-mounted antennas on metallic ground;a joint magnetoelectric sensor and human head model for biomagnetic simulation;a novel time-domain asymptotic solution for a backward transient scattered electric field by a coated metal cylinder;machine-learning for optimization of electrodes and waveforms for electroporation;the tunable single-/narrow-band terahertz metamaterial absorber through photoconductivity;and radiofrequency wave absorption in a graded-index GNP-treated cancer cell substrate inserted in a waveguide.

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Exploring advanced Techniques for Security Testing of sensor Device Chips

Exploring Advanced Techniques for Security Testing of Sensor...

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International conference on Inventive Computing and Informatics (ICICI)

作者： Suye Li Jinan Vocational College Jinan China

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

This study explores advanced techniques for security testing of sensor device chips, critical components in embedded systems and the Internet of Things (IoT). The study emphasizes comprehensive considerations including power management, communication protocol compatibility, and software/hardware interface stability. A review of existing literature highlights significant contributions to improving chip security, multi-factor authentication, data encryption, and intelligent security mechanisms. The proposed methodology focuses on improving hardware security, implementing multi-factor authentication, data encryption, and integrating intelligent security mechanisms for future sensor device chips. Detailed test procedures for sensor device chips are presented, including light source testing, position sensor chip testing, and monitoring system testing. The results contribute to the ongoing development of secure and efficient sensor device chips that are essential for various IoT applications.

关键词： Multi-factor authentication Protocols Embedded systems Reviews Power system management Hardware security Stability analysis

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A Review Paper on Machine Learning Techniques and Its applications in Health Care Sector 1

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2nd International conference on Ubiquitous Computing and Intelligent Information systems (ICUIS)

作者： Gautam, Priya Dehraj, Pooja Noida Inst Engn & Technol Greater Noida India

ISBN: (数字)9789811925412

ISBN: (纸本)9789811925412;9789811925405

Healthcare data analysis has seen a significant rise in recent years and thus becoming a prominent research field. Healthcare data types include sensor data, Clinical data, and Omics data. Clinical data are generally collected whereas a patient is being treated whereas multiple wearable and wireless sensor devices are used for collecting the sensor data. Omics data includes transcriptome, genome, and proteome data types, all of which are complicated and high-dimensional. Since the data type varies and manually dealing with the raw data becomes a challenging task. This is where Machine Learning emerges as a significant tool for analyzing the data. To precisely forecast the healthcare data results, Machine Learning utilizes varied statistical techniques and advanced algorithms. For analysis ML utilizes different algorithms such as Reinforcement Learning, Supervised Learning, and Unsupervised Learning. This paper discusses the Machine learning algorithms of many forms that can be used to analyse and survey enormous volumes of healthcare data.

关键词： Classification algorithm Disease diagnostics Healthcare data Machine learning

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RSM-PA:Research on Route Selection Method of Inter-domain Routing System Based on Path Availability 23

RSM-PA:Research on Route Selection Method of Inter-domain Ro...

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23rd IEEE International conference on High Performance Computing and Communications, 7th IEEE International conference on Data Science and systems, 19th IEEE International conference on Smart City and 7th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhu, Huihu Qiu, Han Zhu, Junhu Wang, Qingxian State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665494571

The inter-domain routing system is the key infrastructure of the Internet. However, BGP does not consider the link state in the routing selection process. As a result, when the inter-domain routing system faces security incidents such as disasters and attacks, it is easy to cause the continuous propagation of link failures, resulting in a large-scale network disconnection and posing a considerable threat to the security of the Internet. The previous research mainly aims to enhance the protocol's safety, cannot change the original failure propagation mechanism, and cannot fundamentally solve cascading failure propagation. In response to this problem, this paper introduces SDN and proposes RSM-PA. This method perceives the available path topology by sharing the link state information in the region, provides a verification mechanism for the availability of the route in the routing process to avoid the link failure in the region due to overload. The comparison of routing results before and after the link state changes under the same experimental conditions shows that RSM-PA can effectively adjust the routing strategy according to the path availability, and lay a solid foundation for suppressing the propagation of cascading failures. © 2021 IEEE.

关键词： Network topology Heuristic algorithms Power system protection Routing Real-time systems Routing protocols Internet

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Airspace Geofencing Volume Sizing with an advanced Air Mobility Vehicle Performance Model 41

Airspace Geofencing Volume Sizing with an Advanced Air Mobil...

引用

41st IEEE/AIAA Digital Avionics systems conference, DASC 2022

作者： Kim, Joseph Liberko, Nicholas Atkins, Ella University of Michigan Robotics Institute United States Collins Aerospace Mission Systems University of Michigan Aiaa Fellow Aerospace Engineering Department and Robotics Department United States

ISBN: (数字)9781665486071

ISBN: (纸本)9781665486071

Airspace geofencing is a key enabler for versatile and safe low-altitude Unmanned Aircraft System (UAS) Traffic Management (UTM). Geofenced airspace volume sizing analysis is necessary to assure efficiency and safety for a broad suite of emerging UAS applications. Airspace safety buffer sizes can be determined and verified by modeling vehicle dynamics as well as quantifying guidance, navigation and control uncertainties. This paper proposes a methodology to design safety buffer sizes given specific vehicle and sensor properties and wind. These parameters are then translated to geofence safety buffer dimensions for straight and turning flight to statistically guarantee an aircraft will stay inside its flight trajectory based keep-in geofence. Vehicle, sensor, and wind parameters are tabulated and analyzed over a prescribed flight trajectory using a Computational Fluid Dynamics (CFD) analysis. Case studies using a small UAS model and a full-size advanced air mobility (AAM) aircraft model provide comparison of geofence volume sizings. © 2022 IEEE.

关键词： Air mobility

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Convolutional Neural Network Classification of Vulnerable Road Users based on Micro-Doppler Signatures using an Automotive Radar 25

Convolutional Neural Network Classification of Vulnerable Ro...

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IEEE 25th International conference on Intelligent Transportation systems (ITSC)

作者： Wachtel, Diogo Edler, Johannes Schroder, Sabine Queiroz, Samuel Huber, Werner TH Ingolstadt Ctr Automot Res Integrated Safety Syst & Measurem Inst Automated Driving CARISSMA IAD Ingolstadt Germany Friedrich Alexander Univ Erlangen Nurnberg FAU Erlangen Germany Inst Tecnol Aeronaut Sao Jose Dos Campos Brazil

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

advanced driver assistance systems (ADAS) are growing in quantity and complexity, requiring even more sensor effectiveness and computational resources. Even though cameras and LiDAR sensors can provide a steady solution in ideal conditions, they are unreliable for adverse weather conditions, such as rain and dense fog. Therefore, radar technology is used for those circumstances is an option to be used for those circumstances. However, its classification accuracy must be enhanced to compete with the other sensor types. This work presents a solution to enhance radar classification quality, adapting a Convolutional Neural Network (CNN) structure to the input of micro-Doppler images of vulnerable road users (VRUs), such as pedestrians, cyclists, and e-scooter drivers. Moreover, two CNNs were trained, each for a particular region of interest (ROIs), one in the near field of the radar until 15m, and the second one up to 25m. The proposed solution presents a promising overall accuracy for its first trial. Nevertheless, it must be further extended to more complex scenes, including more participants, obstacles, and weather conditions.

关键词： radar applications convolutional neural networks object classification

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Finite Element Analysis Study of FBG Magnetostrictive Composite Flux sensor Geometry for Electric Motor Air-gap Flux Monitoring 11

Finite Element Analysis Study of FBG Magnetostrictive Compos...

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and Internet of Things (CPS and IoT)

作者： Suryandi, Asep Andi Tuohy, Paul Djurovic, Sinisa Univ Manchester PTIP TIRBR Natl Res & Innovat Agcy BRIN Dept Elect & Elect Engn Manchester Lancs England Univ Manchester Dept Elect & Elect Engn Manchester Lancs England

ISBN: (纸本)9781665468282

With the progressively more prominent usage of electric motors in a wide range of applications, more advanced monitoring of their operating parameters is becoming increasingly important. The in-service observation of the airgap magnetic flux can be very useful for monitoring the status of permanent magnets, which are key to most modern motors' performance. This was recently shown to be possible through the in-situ application of magnetostrictive composite fibre optic flux sensors. This paper reports an electromagnetic finite element model study exploring the performance of various such sensor configurations and positions in the air-gap of a commercial motor design. The aim of the model study is to identify sensor design and positioning features that can yield an enhanced response in observation of rotor flux. It is shown that rectangular cross-sectional flux sensor geometries provide a considerable advantage in this respect.

关键词： PM motors Finite Element Analysis FBG sensor permanent magnets magnetostrictive composite material terfenol-D powder

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