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

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MS-VAN3T-CARLA: An Open-Source Co-Simulation Framework for Cooperative Perception Evaluation

MS-VAN3T-CARLA: An Open-Source Co-Simulation Framework for C...

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Annual conference on Wireless On Demand Network systems and Services (WONS)

作者： Carlos Mateo Risma Carletti Claudio Casetti Jérôme Härri Fulvio Risso Department of Control and Computer Engineering Politecnico di Torino Turin Italy Communication Systems Department EURECOM Sophia-Antipolis France

The CARLA simulator stands out amongst available open-source simulators providing life-like rendering of vehicular scenarios. While several frameworks, such as OpenCDA [1], have extended CARLA capabilities for the evaluation of cooperative perception applications, a significant gap remains in the use of accurate communication models. To address this need, we present an extension of the ms-van3t simulation framework, based on the ns-3 simulator. It integrates CARLA's high-fidelity sensor and vehicle physics, OpenCDA's data fusion and control automation, with ns-3's advanced communication models. Ms-van3t-CARLA offers a comprehensive tool for researchers working on the evaluation of the effects of vehicular cooperative perception under different communication technologies.

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New Attacks on Cloud Container-Based IoT systems in 5G-advanced and Beyond 9

New Attacks on Cloud Container-Based IoT Systems in 5G-Advan...

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9th IEEE International conference on Electronics, Computing and Communication Technologies, CONECCT 2023

作者： Pimpalkar, Yogita Ravindran, Sharvari Bapat, Jyotsna Das, Debabrata Networking and Communication Research Lab International Institute of Information Technology Electronics City Bangalore560 100 India

ISBN: (纸本)9798350334395

The Internet of Things (IoT) devices generate a large amount of data that get processed in the cloud. Typically, different IoT devices will be allocated to the same Fifth Generation (5G) mobile network slice, on which the IoT services will be using different containers. While cloud containers can offer many benefits, they also introduce new security risks from co-resident containers that can be particularly problematic for IoT devices. The need for long-lasting batteries is essential for the success of wireless-connected IoT devices, particularly in applications where regular battery replacement is impractical or impossible. Energy Depletion Attacks (EDA) can drastically reduce the lifespan of IoT sensor device batteries, whereas Synergistic Power Attacks (SPA) can cause power outages in data centers and disrupt critical services. Although EDA and SPA have been studied in the literature, the IoT cloud information leakages with the advent of network slicing concepts in 5G and 6G leading to these attacks have not been addressed yet. This paper presents comprehensive studies of 5G-advanced IoT cloud framework and related attacks. It reveals novel systematic methods through which powerful stealth Cloud Container-Based EDA (CC-EDA) and Cloud Container-Based SPA (CC-SPA) can be launched. These attacks are difficult to detect as the attacker impersonates a valid IoT management system and manipulates the system's behavior. With a quantitative assessment of the performance of a battery under attack, this paper additionally shows that an aggressive CC-EDA will be deeply damaging and can bring down the entire IoT network within a day. Possible mitigation strategies to address the security concerns associated with IoT cloud-based attacks are proposed. © 2023 IEEE.

关键词： Internet of things

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Micro-, Nanostructural Properties of the MgAl2O3 Ceramics Studied by Combined Methods 16

Micro-, Nanostructural Properties of the MgAl2O3 Ceramics St...

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16th IEEE International conference on advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2022

作者： Klym, Halyna Hadzaman, Ivan Lviv Polytechnic National University Specialized Computer Systems Dpt. Lviv Ukraine Drohobych Ivan Franko State Pedagogical University Physics Dpt. Drohobych Ukraine

ISBN: (纸本)9781665468619

Phase composition, microstructure, porosity in the {MgAl}_{2}mathrm{O}_{4} ceramics sintered at 1200 °C for 2 h for sensor applications in electronics were studied using combined methods (X-ray diffraction, scanning electron microscope, Hg-porosimetry, positron annihilation lifetime spectroscopy). It is shown that the obtained ceramics contains three phases. It has a branched structure of grains, intergranular boundaries and pores with trimodal pore size distribution. It is shown that the presence of water in ceramics is accompanied by more intense capture of positrons on defects near the grain boundaries with additional phases. The presence of water in ceramics leads to the fragmentation of the free volume of nanopores and the additional decomposition of ortho-positronium atoms in the adsorbed water. © 2022 IEEE.

关键词： Nanopores

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19th International conference on Computer Aided systems Theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th International conference on Computer Aided systems Theory, EUROCAST 2024

ISBN: (纸本)9783031829598

The proceedings contain 104 papers. The special focus in this conference is on Computer Aided systems Theory. The topics include: Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance;adaptive Combination in Frequency Domain: An Approach for Robust Nonlinear Acoustic Echo Cancellation;using of a Robotic Platform to Detect Acoustic Events for Indoor Environments;modeling Wildlife Accident Risk with Gaussian Mixture Models;towards a Unified Incident Detection and Response System for Autonomous Transportation;edge-Processing of Myoelectric Signals for the Control of Hand and Arm-Prostheses;AI-Driven Gesture and Action Recognition for Learning Medicine Through Virtual Reality;Medical Protocols and AI-Driven Algorithms for Enhanced Monitoring of Cardiac Implantable Electronic Devices;a Survey of Machine Learning Methods for Analyzing Synovitis Arthritis in Human Joints;motion Tracking in Augmented and Mixed Realities for Healthcare and Medicine applications;advancements and applications of Medical Human Digital Twin Technology in Cerebral Palsy Diagnosis, Therapy, and Rehabilitation;Transformation of IEC 61131-3 onto an Embedded Platform Using LLVM;machine Learning Based Parameter Estimation of Energy Models in Digital Production Environments;efficient Classification of Live sensor Data on Low-Energy IoT Devices with Simple Machine Learning Methods;machine Learning Using a Hybrid Quantum Classical Algorithm with Amplitude Data Encoding;quantitative Trend Analysis of Reinforcement Learning Algorithms in Production systems;Using AutomationML for advanced Simulation in Industrial Automation;AR Digital Twin Demonstrator for Industrial Robotics Education;Accelerating Manual Pick-and-Place Operations with AR-Projected CAD Plans and AI-Assisted Object Recognition;variety Engineering – A Cybernetic Concept with Practical Implications;using a System Archetype to Explore a Business Model for Digital Textile Microfactories;interacting with the Water Cycle -

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Novel Ni-Sn Anode//Lifeop4 Cathode Nanostructures Via Enhanced Deposition for on-Chip Lithium-Ion Micro Batteries

Novel Ni-Sn Anode//Lifeop4 Cathode Nanostructures Via Enhanc...

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Micro and Nanotechnology for Power Generation and Energy Conversion applications (PowerMEMS)

作者： Siyao Jiang Bingmeng Hu Zerui Xu Xiaohong Wang School of Integrated Circuit Tsinghua University Beijing China

ISBN: (数字)9798350380200

ISBN: (纸本)9798350380217

This study presents an advanced method for fabricating on-chip lithium-ion micro batteries, utilizing an optimized electrophoretic deposition process. By employing a three-electrode system, the process ensures precise loading of LiFePO 4 cathode materials, effectively minimizing cross-contamination. The resulting electrodes exhibit a porous microstructure and high specific surface area, facilitating lithium-ion diffusion and promoting robust electrochemical performance. The micro battery demonstrates a plateau of 3.2 V and a capacity of $60.1 \mu \mathrm{Ah}$ $\mathrm{~cm}^{-2}$ after 25 cycles, highlighting its potential for powering miniature energy systems that demand both efficiency and reliability.

关键词： Electric potential Power system stability sensor systems and applications Batteries System-on-chip Nanostructures Wearable devices Wearable sensors Surface treatment Cathodes

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Beyond the Blink: IoT's Next-Gen Drowsiness Detection System for Drivers 3

Beyond the Blink: IoT's Next-Gen Drowsiness Detection System...

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3rd IEEE International conference on Industrial Electronics: Developments and applications, ICIDeA 2025

作者： Routray, Sidheswar Patel, Nachiket Patel, Dhruv Srivastava, Jyoti Dash, Rudra Narayan Pandit Deendayal Energy University Dept. of Computer Science & Engg. Gandhinagar India Indrashil University Dept. of Computer Science & Engg. Mehsana India Ganpat University Dept. of Computer Engineering Mehsana India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (纸本)9798331533205

Drowsiness during driving includes high risks for the driver, the co-passengers, and the other people on the road. Advance Driver Assistance systems (ADAS) have been proposed to reduce these risks. This work introduces a new Internet of Things (IoT) seizure detection system to improve driver safety using Raspberry Pi, which is equipped with various sensors and utilizes machine learning for real-time monitoring and analysis. Using sensor fusion technology, including monitoring yawning and eye-closing patterns, the system aims to detect early signs of driver sleepiness. Being a low-cost, versatile, and tiny device, it becomes an ideal core processor for integration into an in-car environment. Additionally, the simplicity enables seamless communication with various sensors and facilitates effective data collection. Extensive tests and simulations were conducted to evaluate the effectiveness and reliability of the proposed system for real-world driving situations. The result outcomes prove the system's accuracy and efficiency in detecting early signs of driver fatigue to enhance driver safety. The integration of Raspberry Pi and sensor fusion technology makes it economical as well as scalable approaches supporting multiple platforms. © 2025 IEEE.

关键词： advanced driver assistance systems

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Resource Tradeoff Analysis of Plant Physiological Status sensor with Cloud Connectivity 11

Resource Tradeoff Analysis of Plant Physiological Status Sen...

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and applications (IDAACS)

作者： Svilainis, Linas Nakutis, Zilvinas Tervydis, Paulius Chaziachmetovas, Andrius Aleksandrovas, Arturas Kaunas Univ Technol LT-51368 Kaunas Lithuania Kaunas Univ Appl Engn Sci LT-51368 Kaunas Lithuania

ISBN: (纸本)9781665426053

Measurements carried out in the field require power consumption planning so sufficient amount of measurements can be carried out without battery recharge. If instantaneous results report is expected, then communication and data storage, processing resources also have to be proportional to the load expected. Latency of the data transmission, processing and reporting should be maintained within acceptable limits. The plant physiological status estimation system 1 considered in this paper is for field application. It communicates with cloud service using the smartphone as intermediate node. Paper presents the analysis of the power consumption and data latency versus operational modes. Models have been developed, accounting the data acquisition algorithm and data transmission protocols. Analysis results can be used to estimate the sensor and gateway service life from one charge or maximum time between measurement initiation and report delivery. It was found that both sensor and gateway could sustain their operation from one charge over one day operation. As of latency, it was found that single core single server solution can maintain just few users simultaneously. More servers are needed for larger users pool: e.g. 200 servers are required to service 10000 users.

关键词： cloud computing data acquisition equipment data latency power optimization precision agriculture ultrasonic sensors

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advanced Computer-Aided Optimization of Quartz Resonator-Based sensors

Advanced Computer-Aided Optimization of Quartz Resonator-Bas...

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International conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Volodymyr Savchenko Oksana Mnushka Oleg Sokulskyi Computer Engineering and Programming Department National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Information Systems and Technologies Department National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine

ISBN: (数字)9798350378627

ISBN: (纸本)9798350378634

In this study, we present an improved approach to optimizing the parameters of sensor sensing elements using quartz resonators with an interelectrode gap. We combine graphical and analytical methods to solve the multi-criteria optimization problem. The work focuses on the modes of operation of a quartz resonator equipped with an interelectrode gap in sensors with a frequency output, determining a set of optimal parameters and representing them as surfaces in a particular optimization parameter space. The presented results reveal specific areas on the surface of the objective function where optimization of design and technological parameters is possible, taking into account technological influences and features of the sensor design, including the initial value of the interelectrode gap. By using an improved mathematical model for the oscillations of a quartz resonator with an electrode gap, this study achieves results with an accuracy of ($8 . . .11$)% higher than previous studies, demonstrating the effectiveness of the proposed method in improving the design and functionality of piezoelectric sensors for advanced applications.

关键词： Micromechanical devices Electrodes Accuracy Resonant frequency Linear programming Mathematical models sensors

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Characterizing CNN-Based Vessel Detection Algorithm Sensitivity to Optical sensor Artifacts

Characterizing CNN-Based Vessel Detection Algorithm Sensitiv...

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International conference on Machine Learning and applications (ICMLA)

作者： John G. Warner Quinton Davidson Michael Tietz William Scharpf Charles Keene Naval Center for Space Technology US Naval Research Laboratory Washington DC United States

The number of space-based optical imaging systems have substantially grown in recent years. Many of these commercial based vendors are exploring concepts to move processing applications directly to the space segment or to incorporate advanced algorithms in their ground segment. Typically, Convolutional Neural Network (CNN)-based detection algorithms are considered due to their high reliability in laboratory settings. However, this class of algorithms routinely demonstrates degraded performance when unexpected phenomena are introduced to the data. As more near-real-time applications are considered, CNN-based algorithms will be subjected to sensor calibration artifacts. This paper seeks to characterize the response of CNN-based vessel detection algorithms to common electro-optical sensor calibration artifacts. Several artifacts are explored, including added sensor noise and failed detector artifacts. Each of the explored artifacts uniquely impact the algorithm detection performance. It is found that applying Poisson distributed random noise to the imagery substantially degrades model performance by increasing false alarm rate. Likewise, the application of a uniformly distributed random scale factor to the imagery degrades model performance by lowering positive detection rate. These results may inform plans to implement CNN-based algorithms directly in the space-segment by characterizing typical performance variations due to underlying sensor calibration issues.

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19th International conference on Computer Aided systems Theory, EUROCAST 2024

19th International Conference on Computer Aided Systems Theo...

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19th International conference on Computer Aided systems Theory, EUROCAST 2024

ISBN: (纸本)9783031829512

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