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In this contribution, we propose an system setup for the detection andclassification of objects in autonomous driving applications. The recognition algo-rithm is based upon deep neural networks, operating in the 2D image domain. Theresults are combined with data of a stereo camera system to finally incorporatethe 3D object information into our mapping framework. The detection systemis locally running upon the onboard CPU of the vehicle. Several network archi-tectures are implemented and evaluated with respect to accuracy and run-timedemands for the given camera and hardware setup.
The authentication method of electronic devices, based on individual forms of correlograms of their internal electric noises, is well-known. Specific physical differences in the components – for example, caused by variations in production quality – cause specific electrical signals, i.e. electric noise, in the electronic device. It is possible to obtain this information and to identify the specific differences of the individual devices using an embedded analog-to-digital converter (ADC). These investigations confirm the possibility to identify and authenticate electronic devices using bit templates, calculated from the sequence of values of the normalized autocorrelation function of noise. Experiments have been performed using personal computers. The probability of correct identification and authentication increases with increasing noise recording duration. As a result of these experiments, an accuracy of 98.1% was achieved for a 1 second-long registration of EM for a set of investigated computers.
With the increasing degree of interconnectivity in industrial factories, security becomes more and more the most important stepping-stone towards wide adoption of the Industrial Internet of Things (IIoT). This paper summarizes the most important aspects of one keynote of DESSERT2020 conference. It highlights the ongoing and open research activities on the different levels, from novel cryptographic algorithms over security protocol integration and testing to security architectures for the full lifetime of devices and systems. It includes an overview of the research activities at the authors' institute.
Development of Fully Printed Oxide Field-Effect Transistors using Graphene Passive Structures
(2019)
During the past decade to the present time, the topic of printed electronics has gained a lot of attention for their potential use in a number of practical applications, including biosensors, photovoltaic devices, RFIDs, flexible displays, large-area circuits, and so on. To fully realize printed electronic components and devices, effective techniques for the printing of passive structures and electrically and chemically compatible materials in the printed devices need to be developed first. The opportunity of using electrically conducting graphene inks will enable the integration of passive structures into active devices, as for example, printed electrolyte-gated transistors (EGTs). Accordingly, in this study, we present the parametric results obtained on fully printed electrolyte-gated transistors having graphene as the passive electrodes, an inorganic oxide semiconductor as the active channel, and a composite solid polymer electrolyte (CSPE) as the gate insulating material. This configuration offers high chemical and electrical stability while at the same time allowing EGT operation at low potentials, implying the distinct advantage of operation at low input voltages. The printed in-plane EGTs we developed exhibit excellent performance with device mobility up to 16 cm2 V–1 s–1, an ION/IOFF ratio of 105, and a subthreshold slope of 120 mV dec–1.
Fully Printed Inverters using Metal‐Oxide Semiconductor and Graphene Passives on Flexible Substrates
(2020)
Printed and flexible metal‐oxide transistor technology has recently demonstrated great promise due to its high performance and robust mechanical stability. Herein, fully printed inverter structures using electrolyte‐gated oxide transistors on a flexible polyimide (PI) substrate are discussed in detail. Conductive graphene ink is printed as the passive structures and interconnects. The additive printed transistors on PI substrates show an on/off ratio of 106 and show mobilities similar to the state‐of‐the‐art printed transistors on rigid substrates. Printed meander structures of graphene are used as pull‐up resistances in a transistor–resistor logic to create fully printed inverters. The printed and flexible inverters show a signal gain of 3.5 and a propagation delay of 30 ms. These printed inverters are able to withstand a tensile strain of 1.5% following more than 200 cycles of mechanical bending. The stability of the electrical direct current (DC) properties has been observed over a period of 5 weeks. These oxide transistor‐based fully printed inverters are relevant for digital printing methods which could be implemented into roll‐to‐roll processes.
Formal Description of Use Cases for Industry 4.0 Maintenance Processes Using Blockchain Technology
(2019)
Maintenance processes in Industry 4.0 applications try to achieve a high degree of quality to reduce the downtime of machinery. The monitoring of executed maintenance activities is challenging as in complex production setups, multiple stakeholders are involved. So, full transparency of the different activities and of the state of the machine can only be supported, if these stakeholders trust each other. Therefore, distributed ledger technologies, like Blockchain, can be promising candidates for supporting such applications. The goal of this paper is a formal description of business and technical interactions between non-trustful stakeholders in the context of Industry 4.0 maintenance processes using distributed ledger technologies. It also covers the integration of smart contracts for automated triggering of activities.
Purpose
This work presents a new monocular peer-to-peer tracking concept overcoming the distinction between tracking tools and tracked tools for optical navigation systems. A marker model concept based on marker triplets combined with a fast and robust algorithm for assigning image feature points to the corresponding markers of the tracker is introduced. Also included is a new and fast algorithm for pose estimation.
Methods
A peer-to-peer tracker consists of seven markers, which can be tracked by other peers, and one camera which is used to track the position and orientation of other peers. The special marker layout enables a fast and robust algorithm for assigning image feature points to the correct markers. The iterative pose estimation algorithm is based on point-to-line matching with Lagrange–Newton optimization and does not rely on initial guesses. Uniformly distributed quaternions in 4D (the vertices of a hexacosichora) are used as starting points and always provide the global minimum.
Results
Experiments have shown that the marker assignment algorithm robustly assigns image feature points to the correct markers even under challenging conditions. The pose estimation algorithm works fast, robustly and always finds the correct pose of the trackers. Image processing, marker assignment, and pose estimation for two trackers are handled in less than 18 ms on an Intel i7-6700 desktop computer at 3.4 GHz.
Conclusion
The new peer-to-peer tracking concept is a valuable approach to a decentralized navigation system that offers more freedom in the operating room while providing accurate, fast, and robust results.
Machine Learning als Schlüsseltechnologie für Digitalisierung: Wie funktioniert maschinelles Lernen?
(2019)
In diesem Beitrag werden grundlegende Aspekte und Methoden der Data Science erläutert. Nach dem Vorgehensmodell CRISP-DM sind in den Phasen Data Unterstanding und Data Preparation vor allem Verfahren der Datenselektion, Datenvorverarbeitung und der explorativen Datenanalyse anzuwenden. Beim Modeling, der Hauptaufgabe der Data Science, kann man überwachte und unüberwachte Methoden sowie Reinforcement Learning unterscheiden. Auf die Evaluation der Güte eines Modells anhand von Qualitätsmaßen wird anschließend eingegangen. Der Beitrag schließt mit einem Ausblick auf weitere Themen wie Cognitive Computing.
Amorphous In-Ga-Zn-O (IGZO) is a high-mobility semiconductor employed in modern thin-film transistors for displays and it is considered as a promising material for Schottky diode-based rectifiers. Properties of the electronic components based on IGZO strongly depend on the manufacturing parameters such as the oxygen partial pressure during IGZO sputtering and post-deposition thermal annealing. In this study, we investigate the combined effect of sputtering conditions of amorphous IGZO (In:Ga:Zn=1:1:1) and post-deposition thermal annealing on the properties of vertical thin-film Pt-IGZO-Cu Schottky diodes, and evaluated the applicability of the fabricated Schottky diodes for low-frequency half-wave rectifier circuits. The change of the oxygen content in the gas mixture from 1.64% to 6.25%, and post-deposition annealing is shown to increase the current rectification ratio from 10 5 to 10 7 at ±1 V, Schottky barrier height from 0.64 eV to 0.75 eV, and the ideality factor from 1.11 to 1.39. Half-wave rectifier circuits based on the fabricated Schottky diodes were simulated using parameters extracted from measured current-voltage and capacitance-voltage characteristics. The half-wave rectifier circuits were realized at 100 kHz and 300 kHz on as-fabricated Schottky diodes with active area of 200 μm × 200 μm, which is relevant for the near-field communication (125 kHz - 134 kHz), and provided the output voltage amplitude of 0.87 V for 2 V supply voltage. The simulation results matched with the measurement data, verifying the model accuracy for circuit level simulation.
Dementia is a clinical diagnosis reflecting many possible underlying pathologies, for example, vascular dementia and neurodegenerative disorders such as frontotemporal dementia, Lewy body-type disorder or Alzheimer’s disease (AD). The breakthrough of 99mtechnetium-labelled perfusion tracers in the 1990s resulted in many SPECT studies of flow changes in AD. In the first decade of 2000, the role of perfusion SPECT was shifted from diagnosis towards differential diagnosis, parallel to the growing attention for diagnosing early stages of dementia. Previously a diagnosis based largely on a process of exclusion, new guidelines have emerged increasingly employing positive criteria to establish the diagnosis, including neuroimaging biomarkers. Nowadays, FDG PET has largely limited the role of perfusion SPECT, although it is still considered a valuable and cost-effective alternative when PET is not available.
When designing and installing Indoor Positioning Systems, several interrelated tasks have to be solved to find an optimum placement of the Access Points. For this purpose, a mathematical model for a predefined number of access points indoors is presented. Two iterative algorithms for the minimization of localization error of a mobile object are described. Both algorithms use local search technique and signal level probabilities. Previously registered signal strengths maps were used in computer simulation.
One of the challenges for autonomous driving in general is to detect objects in the car's camera images. In the Audi Autonomous Driving Cup (AADC), among those objects are other cars, adult and child pedestrians andemergency vehicle lighting. We show that with recent deep learning networks weare able to detect these objects reliably on the limited Hardware of the model cars. Also, the same deep network is used to detect road features like mid lines, stoplines and even complete crossings. Best results are achieved using Faster R-CNNwith Inception v2 showing an overall accuracy of 0.84 at 7 Hz.
Morphological transition of a rod-shaped phase into a string of spherical particles is commonly observed in the microstructures of alloys during solidification (Ratke and Mueller, 2006). This transition phenomenon can be explained by the classic Plateau-Rayleigh theory which was derived for fluid jets based on the surface area minimization principle. The quintessential work of Plateau-Rayleigh considers tiny perturbations (amplitude much less than the radius) to the continuous phase and for large amplitude perturbations, the breakup condition for the rod-shaped phase is still a knotty issue. Here, we present a concise thermodynamic model based on the surface area minimization principle as well as a non-linear stability analysis to generalize Plateau-Rayleigh’s criterion for finite amplitude perturbations. Our results demonstrate a breakup transition from a continuous phase via dispersed particles towards a uniform-radius cylinder, which has not been found previously, but is observed in our phase-field simulations. This new observation is attributed to a geometric constraint, which was overlooked in former studies. We anticipate that our results can provide further insights on microstructures with spherical particles and cylinder-shaped phases.
The visualization of heart rhythm disturbance and atrial fibrillation therapy allows the optimization of new cardiac catheter ablations. With the simulation software CST (Computer Simulation Technology, Darmstadt) electromagnetic and thermal simulations can be carried out to analyze and optimize different heart rhythm disturbance and cardiac catheters for pulmonary vein isolation. Another form of visualization is provided by haptic, three-dimensional print models. These models can be produced using an additive manufacturing method, such as a 3d printer. The aim of the study was to produce a 3d print of the Offenburg heart rhythm model with a representation of an atrial fibrillation ablation procedure to improve the visualization of simulation of cardiac catheter ablation. The basis of 3d printing was the Offenburg heart rhythm model and the associated simulation of cryoablation of the pulmonary vein. The thermal simulation shows the pulmonary vein isolation of the left inferior pulmonary vein with the cryoballoon catheter Arctic Front Advance™ from Medtronic. After running through the simulation, the thermal propagation during the procedure was shown in the form of different colors. The three-dimensional print models were constructed on the base of the described simulation in a CAD program. Four different 3d printers are available for this purpose in a rapid prototyping laboratory at the University of Applied Science Offenburg. Two different printing processes were used and a final print model with additional representation of the esophagus and internal esophagus catheter was also prepared for printing. With the help of the thermal simulation results and the subsequent evaluation, it was possible to draw a conclusion about the propagation of the cold emanating from the catheter in the myocardium and the surrounding tissue. It was measured that just 3 mm from the balloon surface into the myocardium the temperature dropped to 25 °C. The simulation model was printed using two 3d printing methods. Both methods, as well as the different printing materials offer different advantages and disadvantages. All relevant parts, especially the balloon catheter and the conduction, are realistically represented. Only the thermal propagation in the form of different colors is not shown on this model. Three-dimensional heart rhythm models as well as virtual simulations allow very clear visualization of complex cardiac rhythm therapy and atrial fibrillation treatment methods. The printed models can be used for optimization and demonstration of cryoballoon catheter ablation in patients with atrial fibrillation.
Um medizinische Behandlungsverfahren in der Praxis besser verstehen und anwenden zu können, gewinnt die Visualisierung der Prozesse an immer größerer Bedeutung. Durch Anwendung der Computer-Simulationssoftware CST können elektromagnetische und thermische Simulationen zur Analyse verschiedener Herzrhythmusstörungen durchgeführt werden. Eine weitere Form der Visualisierung erfolgt durch haptische, dreidimensionale Druckmodelle. Diese Modelle können mit einem generativen Herstellungsverfahren, wie z. B. einem 3D-Drucker, in kürzester Zeit hergestellt werden.
Abstract: 3D print of heart rhythm model with cryoballoon catheter ablation of pulmonary vein
(2019)
The visualization of heart rhythm disturbance and atrial fibrillation therapy allow the optimization of new cardiac catheter ablations. With the simulation software CST (Computer Simulation Technology, Darmstadt) electromagnetic and thermal simulations can be carried out to analyze and optimize different heart rhythm disturbance and cardiac catheters for pulmonary vein isolation. Another form of visualization is provided by haptic, three-dimensional print models. These models can be produced using an additive manufacturing method, such as a 3D printer. The aim of the study was to produce a 3D print of the Offenburg heart rhythm model with a representation of an atrial fibrillation ablation procedure to improve the visualization of simulation of cardiac catheter ablation.
The basis of 3D printing was the Offenburg heart rhythm model and the associated simulation of cryoablation of the pulmonary vein. The thermal simulation shows the pulmonary vein isolation of the left inferior pulmonary vein with the cryoballoon catheter Arctic Front AdvanceTM from Medtronic. After running through the simulation, the thermal propagation during the procedure was shown in the form of different colors. The three-dimensional print models were constructed on the base of the described simulation in a CAD program. Four different 3D printers are available for this purpose in a rapid prototyping laboratory at the University of Applied Science Offenburg. Two different printing processes were used: 1. a binder jetting printer with polymer gypsum and 2. a multi-material printer with photopolymer. A final print model with additional representation of the esophagus and internal esophagus catheter was also prepared for printing.
With the help of the thermal simulation results and the subsequent evaluation, it was possible to make a conclusion about the propagation of the cold emanating from the catheter in the myocardium and the surrounding tissue. It could be measured that already 3 mm from the balloon surface into the myocardium the temperature drops to 25 °C. The simulation model was printed using two 3D printing methods. Both methods as well as the different printing materials offer different advantages and disadvantages. While the first model made of polymer gypsum can be produced quickly and cheaply, the second model made of photopolymer takes five times longer and was twice as expensive. On the other hand, the second model offers significantly better properties and was more durable overall. All relevant parts, especially the balloon catheter and the conduction, are realistically represented. Only the thermal propagation in the form of different colors is not shown on this model.
Three-dimensional heart rhythm models as well as virtual simulations allow a very good visualization of complex cardiac rhythm therapy and atrial fibrillation treatment methods. The printed models can be used for optimization and demonstration of cryoballoon catheter ablation in patients with atrial fibrillation.
In many application domains, in particular automotives, guaranteeing a very low failure rate is crucial to meet functional and safety standards. Especially, reliable operation of memory components such as SRAM cells is of essential importance. Due to aggressive technology downscaling, process and runtime variations significantly impact manufacturing yield as well as functionality. For this reason, a thorough memory failure rate assessment is imperative for correct circuit operation and yield improvement. In this regard, Monte Carlo simulations have been used as the conventional method to estimate the variability induced failure rate of memory components. However, Monte Carlo methods become infeasible when estimating rare events such as high-sigma failure rates. To this end, Importance Sampling methods have been proposed which reduce the number of required simulations substantially. However, existing methods still suffer from inaccuracies and high computational efforts, in particular for high-sigma problems. In this paper, we fill this gap by presenting an efficient mixture Importance Sampling approach based on Bayesian optimization, which deploys a surface model of the objective function to find the most probable failure points. Its advantages include constant complexity independent of the dimensions of design space, the potential to find the global extrema, and higher trustworthiness of the estimated failure rate by accurately exploring the design space. The approach is evaluated on a 6T-SRAM cell as well as a master-slave latch based on a 28nm FDSOI process. The results show an improvement in accuracy, resulting in up to 63× better accuracy in estimating failure rates compared to the best state-of-the-art solutions on a 28nm technology node.
Neuromorphic computing systems have demonstrated many advantages for popular classification problems with significantly less computational resources. We present in this paper the design, fabrication and training of a programmable neuromorphic circuit, which is based on printed electrolytegated field-effect transistor (EGFET). Based on printable neuron architecture involving several resistors and one transistor, the proposed circuit can realize multiply-add and activation functions. The functionality of the circuit, i.e. the weights of the neural network, can be set during a post-fabrication step in form of printing resistors to the crossbar. Besides the fabrication of a programmable neuron, we also provide a learning algorithm, tailored to the requirements of the technology and the proposed programmable neuron design, which is verified through simulations. The proposed neuromorphic circuit operates at 5V and occupies 385mm 2 of area.
The Internet of Things (IoT) application has becoming progressively in-demand, most notably for the embedded devices (ED). However, each device has its own difference in computational capabilities, memory usage, and energy resources in connecting to the Internet by using Wireless Sensor Networks (WSNs). In order for this to be achievable, the WSNs that form the bulk of the IoT implementation requires a new set of technologies and protocol that would have a defined area, in which it addresses. Thus, IPv6 Low Power Area Network (6LoWPAN) was designed by the Internet Engineering Task Force (IETF) as a standard network for ED. Nevertheless, the communication between ED and 6LoWPAN requires appropriate routing protocols for it to achieve the efficient Quality of Service (QoS). Among the protocols of 6LoWPAN network, RPL is considered to be the best protocol, however its Energy Consumption (EC) and Routing Overhead (RO) is considerably high when it is implemented in a large network. Therefore, this paper would propose the HRPL to enchance the RPL protocol in reducing the EC and RO. In this study, the researchers would present the performance of RPL and HRPL in terms of EC, Control traffic Overhead (CTO) and latency based on the simulation of the 6LoWPAN network in fixed environment using COOJA simulator. The results show HRPL protocol achieves better performance in all the tested topology in terms of EC and CTO. However, the latency of HRPL only improves in chain topology compared with RPL. We found that further research is required to study the relationship between the latency and the load of packet transmission in order to optimize the EC usage.
The development of Internet of Things (IoT) embedded devices is proliferating, especially in the smart home automation system. However, the devices unfortunately are imposing overhead on the IoT network. Thus, the Internet Engineering Task Force (IETF) have introduced the IPv6 Low-Power Wireless Personal Area Network (6LoWPAN) to provide a solution to this constraint. 6LoWPAN is an Internet Protocol (IP) based communication where it allows each device to connect to the Internet directly. As a result, the power consumption is reduced. However, the limitation of data transmission frame size of the IPv6 Routing Protocol for Low-power and Lossy Network’s (RPL’s) had made it to be the running overhead, and thus consequently degrades the performance of the network in terms of Quality of Service (QoS), especially in a large network. Therefore, HRPL was developed to enhance the RPL protocol to minimize redundant retransmission that causes the routing overhead. We introduced the T-Cut Off Delay to set the limit of the delay and the H field to respond to actions taken within the T-Cut Off Delay. Thus, this paper presents the comparison performance assessment of HRPL between simulation and real-world scenarios (6LoWPAN Smart Home System (6LoSH) testbed) in validating the HRPL functionalities. Our results show that HRPL had successfully reduced the routing overhead when implemented in 6LoSH. The observed Control Traffic Overhead (CTO) packet difference between each experiment is 7.1%, and the convergence time is 9.3%. Further research is recommended to be conducted for these metrics: latency, Packet Delivery Ratio (PDR), and throughput.
Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
A physical unclonable function (PUF) is a hardware circuit that produces a random sequence based on its manufacturing-induced intrinsic characteristics. In the past decade, silicon-based PUFs have been extensively studied as a security primitive for identification and authentication. The emerging field of printed electronics (PE) enables novel application fields in the scope of the Internet of Things (IoT) and smart sensors. In this paper, we design and evaluate a printed differential circuit PUF (DiffC-PUF). The simulation data are verified by Monte Carlo analysis. Our design is highly scalable while consisting of a low number of printed transistors. Furthermore, we investigate the best operating point by varying the PUF challenge configuration and analyzing the PUF security metrics in order to achieve high robustness. At the best operating point, the results show areliability of 98.37% and a uniqueness of 50.02%, respectively. This analysis also provides useful and comprehensive insights into the design of hybrid or fully printed PUF circuits. In addition, the proposed printed DiffC-PUF core has been fabricated with electrolyte-gated field-effect transistor technology to verify our design in hardware.
Novel manufacturing technologies, such as printed electronics, may enable future applications for the Internet of Everything like large-area sensor devices, disposable security, and identification tags. Printed physically unclonable functions (PUFs) are promising candidates to be embedded as hardware security keys into lightweight identification devices. We investigate hybrid PUFs based on a printed PUF core. The statistics on the intra- and inter-hamming distance distributions indicate a performance suitable for identification purposes. Our evaluations are based on statistical simulations of the PUF core circuit and the thereof generated challenge-response pairs. The analysis shows that hardware-intrinsic security features can be realized with printed lightweight devices.
In users of a cochlear implant (CI) together with a contralateral hearing aid (HA), so-called bimodal listeners, differences in processing latencies between digital HA and CI up to 9 ms constantly superimpose interaural time differences. In the present study, the effect of this device delay mismatch on sound localization accuracy was investigated. For this purpose, localization accuracy in the frontal horizontal plane was measured with the original and minimized device delay mismatch. The reduction was achieved by delaying the CI stimulation according to the delay of the individually worn HA. For this, a portable, programmable, battery-powered delay line based on a ring buffer running on a microcontroller was designed and assembled. After an acclimatization period to the delayed CI stimulation of 1 hr, the nine bimodal study participants showed a highly significant improvement in localization accuracy of 11.6% compared with the everyday situation without the delay line (p < .01). Concluding, delaying CI stimulation to minimize the device delay mismatch seems to be a promising method to increase sound localization accuracy in bimodal listeners.
RETIS – Real-Time Sensitive Wireless Communication Solution for Industrial Control Applications
(2020)
Ultra-Reliable Low Latency Communications (URLLC) has been always a vital component of many industrial applications. The paper proposes a new wireless URLLC solution called RETIS, which is suitable for factory automation and fast process control applications, where low latency, low jitter, and high data exchange rates are mandatory. In the paper, we describe the communication protocol as well as the hardware structure of the network nodes for implementing the required functionality. Many techniques enabling fast, reliable wireless transmissions are used – short Transmission Time Interval (TTI), Time-Division Multiple Access (TDMA), MIMO, optional duplicated data transfer, Forward Error Correction (FEC), ACK mechanism. Preliminary tests show that reliable end-to-end latency down to 350 μs and packet exchange rate up to 4 kHz can be reached (using quadruple MIMO and standard IEEE 802.15.4 PHY at 250 kbit/s).