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IEEE Conference on Dependable and Secure Computing

作者： Sinan Yavuz Edwin Naroska Kai Daniel Department of Electrical Engineering and Computer Science University of Siegen Siegen Germany Department of Electrical Engineering and Computer Science Niederrhein University of Applied Sciences Krefeld Germany Institute of Measurement and Sensor Technology University of Applied Sciences Ruhr West Mülheim Germany

ISBN: (数字)9798331540289

ISBN: (纸本)9798331540296

The security of IoT (Internet of Things) devices and the protection of sensitive information processed by these devices such as personal data, sensor values, process-related information is an important and difficult challenge. A major task in IoT communication is secure identification of devices. Unfortunately, traditional cryptographic methods are often not suitable for IoT devices due to their limited hardware resources. However, typical methods are computationally intensive, require a large amount of memory, and have a high-power consumption. On the other hand, Physical Unclonable Functions (PUFs) are low-cost and lightweight hardware-based primitives that can be used as a security component to protect data against third parties and thus increase security of a device. In this paper, the challenges and vulnerabilities in the development of PUF-based authentication protocols are presented. To this end, a security analysis of different approaches known from literature are discussed. Furthermore, possible attack vectors and prevention techniques are also considered.

关键词： Protocols Reviews Authentication Physical unclonable function Vectors Security Internet of Things Servers Object recognition Field programmable gate arrays

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Development of a 2–4 Double Arbiter PUF Design on FPGA with Enhanced Performance

Development of a 2–4 Double Arbiter PUF Design on FPGA with...

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IEEE sensorS

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Implementation of delay-based Physical Unclonable Functions (PUFs) on FPGAs poses significant challenges due to high requirements, such as the generation of unique and reliable keys. These requirements must be fulfilled, especially when using PUFs in security applications, otherwise security cannot be guaranteed. In addition, it must be ensured that physical disturbances such as fluctuations in the ambient temperature do not have a major impact on the performance of the PUF and therefore on security. In this paper, the implementation and evaluation of a novel 56-bit 2–4 Double Arbiter PUF (DAPUF) is presented. For performance analysis, the proposed 2–4 DAPUF is investigated with 20 Digilent Nexys-3 (AMD-Xilinx Spartan-6 FPGA) boards and a large data set of 30 million challenges under varying ambient temperature in the range from 0°C to 50°C. Our experimental results show that the proposed 2–4 DAPUF is resistant to temperature fluctuations. Here, the maximum change in reliability amounts to 1.18 %. For randomness and uniqueness, the changes are less than 0.50 %. Furthermore, our results show that performance can be significantly improved by combining PUFs with XOR operations.

关键词： Resistance Temperature distribution Fluctuations Physical unclonable function sensors Performance analysis Security Field programmable gate arrays

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Data Protection Regulation Compliant Dataset Generation for LiDAR-Based People Detection Using Neural Networks

Data Protection Regulation Compliant Dataset Generation for ...

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AI, Science, engineering, and technology (AIxSET), Conference on

作者： Lukas Haas Johann Zedelmeier Florian Bindges Matthias Kuba Thomas Zeh Martin Jakobi Alexander W. Koch Institute for Driver Assistance Systems and Connected Mobility Kempten University of Applied Sciences Germany Institute for Measurement Systems and Sensor Technology Technical University of Munich Germany Blickfeld GmbH Munich Germany Faculty of Electrical Engineering Kempten University of Applied Sciences Germany

ISBN: (数字)9798350390995

ISBN: (纸本)9798350391008

The use of LiDAR sensor technology for people detection offers a significant advantage in terms of data pro-tection. In LiDAR point clouds, unlike camera images, people can be detected but not identified without further information. LiDAR sensors are, therefore, particularly suitable for detecting people in publicly accessible places and reacting accordingly to the number of people, for example, with on demand services at airports. Due to the anonymity of people in LiDAR point clouds, personal data is protected, and approval for implementing such a detection system is simpler than that of comparable camera systems. In this paper, we present a measurement setup that covers the configuration of the sensor setup, the creation of a dataset for training neural networks for object detection, and the object detection itself. The measurement setup generates an average of 2408 automatically labeled point clouds per sensor, per hour. The SECOND network trained with this dataset achieves average precision for the intersection over union of the 2D view with a threshold of 0.5 of 87.67 %, the PV-RCNN of 85.74 % and an average precision for the average orientation similarity with a threshold of 0.5 of 89.56 %, and for the PV-RCNN of 87.81 %.

关键词： Point cloud compression Training Laser radar Three-dimensional displays Neural networks Data protection Object detection Cameras Software Regulation

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Characterization and Operation of Graphene-Oxide-Semiconductor Emitters at Atmospheric Pressure Levels

Characterization and Operation of Graphene-Oxide-Semiconduct...

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International Conference on Vacuum Nanoelectronics (IVNC)

作者： Florian Herdl Maximillian J. Kueddelsmann Andreas Schels Michael Bachmann Simon Edler Dominik Wohlfartsstätter Felix Düsberg Alexander Prugger Michael Dillig Florian Dams Rupert Schreiner Cormac Ó Coileáin Stefan Zimmermann Andreas Pahlke Georg S. Duesberg Center for Integrated Sensor Systems University of the Bundeswehr Munich Institute of Physics Germany Leibniz University Hannover Institute of Electrical Engineering and Measurement Technology Germany KETEK GmbH Munich Germany Ostbayerische Technische Hochschule Regensburg Germany

In recent years Graphene-Oxide-Semiconductor (GOS) electron emitters have attracted a lot of interest due to their outstanding durability in modest vacuum conditions. However, the performance at ambient pressure remains largely unexplored. In this study GOS-emitters are characterized in nitrogen and air at atmospheric pressure, and compared with their vacuum characteristics. For this purpose, lifetime and IV-characteristics measurements are shown. Furthermore, the GOS-emitter was operated as an ionization source for ion mobility spectrometry (IMS) at ambient conditions.

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Usability Tests on the Temperature-Induced Changes in Magnetic Hysteresis During Steel Production

Usability Tests on the Temperature-Induced Changes in Magnet...

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Impedance Spectroscopy (IWIS), International Workshop on

作者： Marc Simoneit Jonas Brodmann Stephan Schulze Andreas Hennig Jörg Himmel Institute for Measurement Engineering and Sensor Technology University of Applied Sciences Ruhr West Mülheim a. d. Ruhr Germany Senior Expert Research & Development SMS Group GmbH Düsseldorf Germany

This paper presents an inductive measuring system using a two-pancake coil setup for monitoring the electromagnetic properties of steel sheets. An experimental setup was developed to perform measurements on cooling sheet metal samples during real structural transformations. Additional to the experiments with hot steel sheets, a simulation in COMSOL Multiphysics was used to validate the measurement results. The experiments conducted with the cooling material confirmed the suitability of the measurement system for the application described. The results obtained in this work show that by evaluating the phase shift between the exciting magnetic field H and the induction B, the structural transformation can be reliably monitored. In this work, a phase shift of 2 degrees was measured when a steel sheet was cooled by about 200 degrees Celsius.

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Inductive sensor for Magnetic Property Evaluation in Hot Rolling Mill Wire Production

Inductive Sensor for Magnetic Property Evaluation in Hot Rol...

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Impedance Spectroscopy (IWIS), International Workshop on

作者： Jonas Brodmann Marc Simoneit Stephan Schulze Andreas Hennig Jörg Himmel Institute for Measurement Engineering and Sensor Technology Ruhr West University of Applied Sciences Mülheim a. d. Ruhr Germany Senior Expert Research & Development SMS Group GmbH Düsseldorf Germany

This paper presents the results of a preliminary investigation for the development of an inductive sensor system for in-situ measurements in hot rolling mill steel wire production. The developed system should monitor the surface layer of the wire concerning changes in the microstructural composition using magnetic property evaluation. The sensor consists of two surrounding coils and evaluates a measure related to the slope of the commutation curve around the origin of the coordinate system This presented preliminary investigation discussed, whether the evaluation of the AC commutation curve under nonnegligible eddy currents is suitable to distinguish between two different microstructures. In addition, it was investigated, whether the measurement concept remains valid under plant conditions with high temperatures up to 600 °C. Within this work, two samples of 17 mm diameter and 175 mm length with different microstructural compositions could be distinguished under laboratory conditions at room temperature and in high-temperature experiments. The results could be plausibilized using the virgin magnetization curve in COMSOL Multiphysics, which was modified to model the magnetic behavior of the material for higher temperatures.

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VelObPoints: a Neural Network for Vehicle Object Detection and Velocity Estimation for Scanning LiDAR sensors

VelObPoints: a Neural Network for Vehicle Object Detection a...

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IEEE sensorS

作者： Lukas Haas Nico Leuze Arsalan Haider Matthias Kuba Thomas Zeh Alfred Schöttl Martin Jakobi Alexander W. Koch Institute for Driver Assistance Systems and Connected Mobility Kempten University of Applied Sciences Germany Institute for Measurement Systems and Sensor Technology Technical University of Munich Germany Institute for Applications of Machine Learning and Intelligent Systems University of Applied Sciences Munich Germany Faculty of Electrical Engineering University of Applied Sciences Kempten Germany

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

LiDAR sensors are crucial sensors for highly automated vehicles. Relevant information about the vehicle's sur-roundings can be obtained from 3D point clouds, which serves as a basis for decision-making for further control of the vehicle. For this purpose, information about the type and position of objects in the vehicle's environment and their velocity and movement direction is essential. In this paper, we present VelObPoints, a neural network architecture that estimates the longitudinal and lateral velocity and performs object detection on a single LiDAR point cloud. Compared to existing tracking methods, the neural network allows this information to be extracted from a single LiDAR frame. We propose a simulated dataset for training and testing, containing motion distortion effects. The neural network achieves a mean Intersection over Union of 0.863 and a mean average velocity error of 0.332 m s −l . Based on a single point cloud, this information, consisting of the object's scaling, position, and rotation, as well as its velocities in the longitudinal and lateral directions, is immediately available for the driving function. For subsequent motion prediction, and object tracking, leading to more quickly available velocity and motion direction information and higher redundancy in sensor data fusion.

关键词： Point cloud compression Laser radar Three-dimensional displays Neural networks Data integration sensor fusion Distortion sensor systems sensors Object tracking

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Full-Waveform Modeling for Time-of-Flight measurements based on Arrival Time of Photons

arXiv

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arXiv 2022年

作者： Fink, Maximilian Schardt, Michael Baier, Valentin Wang, Kun Jakobi, Martin Koch, Alexander W. Technical University of Munich Department of Electrical and Computer Engineering Institute for Measurement Systems and Sensor Technology Munich80333 Germany Blickfeld GmbH Munich80339 Germany

Modern LiDAR sensors find increasing use in safety-critical applications. Therefore, highly accurate modeling of the system’s behavior under demanding environmental conditions is necessary. In this paper, we present a modular structure to accurately simulate the amplified raw detector signal of a direct time-of-flight LiDAR system for coaxial transmitter-receiver optics. Our model describes, a measurement system based on standard optical components and a detector able of converting single photons to an electrical signal. To verify the model’s predictions, single-point measurements for targets of different reflectivity at defined distances were performed. Statistical analysis shows an R-squared value greater than 0.990 for simulated and measured signal amplitude levels. Noise modeling shows good accordance with the performed measurements for different target irradiance levels. The presented results have a guiding significance in the modeling of the complex signal processing chain of LiDAR systems, as it enables the prediction of key parameters of the system early in the development process. Hence, unnecessary costs by design flaws can be mitigated. The modular structure allows easy adaption for arbitrary LiDAR systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Optical radar

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Planar mapping of the liquid fraction of froth using ultrasound Flächige Darstellung des Wassergehaltes von Schaum mittels Ultraschall 21

Planar mapping of the liquid fraction of froth using ultraso...

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21. ITG/GMA-Fachtagung sensoren und Messsysteme - 21st ITG/GMA Conference on sensors and Measuring Systems

作者： Emmerich, Hannes Knüpfer, Leon Trtik, Pavel Eckert, Kerstin Heitkam, Sascha Starke, Eric Weik, David Büttner, Lars Czarske, Jürgen Technical University Dresden Laboratory of Measurement and Sensor System Techniques Dresden01069 Germany Helmholtz-Zentrum Dresden-Rossendorf Institute of Fluid Dynamics Dresden01328 Germany Paul Scherrer Institut Laboratory for Neutron Scattering and Imaging Villigen5232 Switzerland Technical University Dresden Institute of Process Engineering and Environmental Technology Dresden01069 Germany SICK Engineering GmbH Bergener Ring 27 Ottendorf-Okrilla01458 Germany

ISBN: (纸本)9783800758364

Flotation processes are essential processes for resource separation, the monitoring of which can save vast amounts of water and energy. To control them, it is necessary to measure the phase fractions present in the froth. Currently, no suitable measurement method exists that can be easily integrated into the existing process and has a penetration depth of more than 5 cm. Therefore, in this paper we present a measurement system for determining the liquid distribution in foam using ultrasound. To counteract the strong attenuating effect of the foam on the ultrasound, we use low-frequency probes with a center frequency of 135 kHz. Electrodes determine an integral liquid fraction by conductivity measurement. Within a liquid range of 0.17 ·10−2 to 0.82 ·10−2, the measurement system was first calibrated for a penetration depth of 9.2 cm and validated by simultaneous neutron imaging. An absolute and relative measurement uncertainty of 0.23 ·10−2 and 42.5 % was the respective result. A resolution of 7.5 mm in the axial, 13 mm in lateral direction and 1 Hz in time were obtained. In a dynamic inhomogeneous case, the measurement system was additionally validated for a use case. This investigation represents a first step towards process optimization in flotation processes. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Ultrasonics

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Corner loading and its influence on the tilt sensitivity of precision weighing cells 20

Corner loading and its influence on the tilt sensitivity of ...

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20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020

作者： Darnieder, Maximilian Pabst, Markus Fröhlich, Thomas Theska, René Institute for Design and Precision Engineering Precision Engineering Group Technische Universität Ilmenau Department of Mechanical Engineering Institute for Process Measurement and Sensor Technology Process Measurement Technology Group Technische Universität Ilmenau Department of Mechanical Engineering

ISBN: (纸本)9780995775176

Corner loading and ground tilt are relevant error sources for precision weighing cells. The sensitive compliant mechanism of the weighing cell is subject to large dead weights with the aim to resolve small mass differences. Tilting of the base or an eccentric load application relative to the centre of the weighing pan result in lateral force components, apart from those in measurement direction. This changes the indication of the balance resulting in measurement errors. In this paper, a finite element model of the weighing cell was used to evaluate the corner load sensitivity in three directions and the tilt sensitivity in two directions. Based on a parametric study, an optimal attachment point for the weighing cell was found where all considered mechanical errors can be reduced to second order effects. Copyright © Proceedings of the 20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020. All rights reserved.

关键词： Cytology

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