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Electrolyte-gated transistors (EGTs) represent an interesting alternative to conventional dielectric-gating to reduce the required high supply voltage for printed electronic applications. Here, a type of ink-jet printable ion-gel is introduced and optimized to fabricate a chemically crosslinked ion-gel by self-assembled gelation, without additional crosslinking processes, e.g., UV-curing. For the self-assembled gelation, poly(vinyl alcohol) and poly(ethylene-alt-maleic anhydride) are used as the polymer backbone and chemical crosslinker, respectively, and 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([EMIM][OTf]) is utilized as an ionic species to ensure ionic conductivity. The as-synthesized ion-gel exhibits an ionic conductivity of ≈5 mS cm−1 and an effective capacitance of 5.4 µF cm−2 at 1 Hz. The ion-gel is successfully employed in EGTs with an indium oxide (In2O3) channel, which shows on/off-ratios of up to 1.3 × 106 and a subthreshold swing of 80.62 mV dec−1.
Sweaty has already participated four times in RoboCup soccer competitions (Adult Size) and came second three times. While 2016 Sweaty needed a lot of luck to be finalist, 2017 Sweaty was a serious adversary in the preliminary rounds. In 2018 Sweaty showed up in the final with some lack of experience and room for improvements, but not without any chance. This paper describes the intended improvements of the humanoid adult size robot Sweaty in order to qualify for the RoboCup 2019 adult size competition.
Hochspannungs-Mischstrom-Übertragung (HMÜ) - Eine Ergänzung zu bestehenden Übertragungstechnologien?
(2019)
Bei der Mischstromübertragung wird einem Wechselstrom direkt ein Gleichstrom überlagert. Wechselstrom und Gleichstrom werden also auf dem gleichen Seil geführt.
Dadurch könnten die bereits bestehenden Drehstrom-Übertragungs-Strecken des Übertragungsnetzes genutzt werden.
Durch eine Aufschaltung des Gleichstromes auf vorhandene Freileitungen kann theoretisch bei kurzen Leitungen (<150km) bis zu 50% mehr Wirkleistung und bei großen Übertragungsstrecken (>300km) in etwa eine Verdopplung der übertragbaren Wirkleistung erwartet werden.
Theoretisch betrachtet ist die Mischstrom-Übertragung eine geometrische Addition aller Strom- und Spannungskomponenten, was zu einer Erhöhung der Leiter-Erde-Spannung führt, ohne dabei Einfluss auf die verkettete Spannung zu nehmen.
Außerdem wird die Übertragung von Blindströmen unnötig, da ein natürlicher Betrieb von Leitungen des HDÜ-Netzes empfehlenswert ist.
Die theoretischen Betrachtungen konnten mathematisch bewiesen und die technische Umsetzung mit einem 1:1000-Modellsystem demonstriert und bestätigt werden.
Wireless sensor networks have found their way into a wide range of applications, among which environmental monitoring systems have attracted increasing interests of researchers. Main challenges for these applications are scalability of the network size and energy efficiency of the spatially distributed nodes. Nodes are mostly battery-powered and spend most of their energy budget on the radio transceiver module. In normal operation modes most energy is spent waiting for incoming frames. A so-called Wake-On-Radio (WOR) technology helps to optimize trade-offs between energy consumption, communication range, complexity of the implementation and response time. We already proposed a new protocol called SmartMAC that makes use of such WOR technology. Furthermore, it gives the possibility to balance the energy consumption between sender and receiver nodes depending on the use case. Based on several calculations and simulations, it was predicted that the SmartMAC protocol was significantly more efficient than other schemes being proposed in recent publications, while preserving a certain backward compatibility with standard IEEE802.15.4 transceivers. To verify this prediction, we implemented the SmartMAC protocol for a given hardware platform. This paper compares the realtime performance of the SmartMAC protocol against simulation results, and proves the measured values are very close to the estimated values. Thus we believe that the proposed MAC algorithms outperforms all other Wake-on-Radio MACs.
Ziel der Thesis war zuerst eine kurze Literatur-Recherche und eine Einarbeitung in die Automatisierungstechnik (insbesondere in Robotik, speicherprogrammierbare Steuerungen, Bildverarbeitung und Kommunikationsmöglichkeiten), dann die Konzeption und der Aufbau eine Schulungszelle, mit der die Studenten in die Praxis umsetzen können, was sie im Labor gelernt haben und am Ende die Herstellung von Schulungsunterlagen.
Dafür wurde eine mehrstufige Lösung ausgewählt und betrachtet. Diese Lösung besteht in erster Linie in der Erforschung über die verschiedenen verfügbaren Komponenten. das heißt, die Bedienung und die Programmierung eines Universalroboters(UR5e), einer Sensopart-Kamera, eines Wago-PLC mit der Festo Pick-Place didaktisch Station und natürlich die Steuerung ihrer verschiedenen Software zu beherrschen. Dann folgen die Konzeption und der Aufbau der Schulungszelle, die Programmierung einer didaktischen Applikation, die den Studenten als Beispiel dient, und schließlich die Erstellung einer Anleitung dieser Applikation.
Die vorliegende Bachelorarbeit beschäftigt sich mit der Evaluation einer Simulationssoftware anhand unterschiedlichen Roboterkinematiken sowie einer virtuellen Inbetriebnahme einer speicherprogrammierbaren Steuerung (SPS) mittels OPC-UA-Kommunikation.
Für die Evaluation der Simulationssoftware wurden drei Roboter verschiedener Hersteller, die die gleiche Aufgabe erfüllen, mit der Simulationssoftware Visual Components simuliert und anschließend in einer realen Umgebung getestet. Für die virtuelle Inbetriebnahme einer SPS mittels OPC-UA-Kommunikation wurde eine virtuelle SPS-gesteuerte Roboter-Fertigungslinie implementiert.
Ergebnis dieser Arbeit sind detaillierte Einarbeitung in die Simulationssoftware Visual Components, strukturierte Offline und Online Roboterprogrammierung und somit Auswertung der Simulationssoftware anhand unterschiedlicher Roboterkinematiken. Bewertung des Datenaustauschs (via OPC-UA) zwischen einer SPS und der Simulationssoftware Visual Components.
Amongst all the major hazard aspects for the health of people in big conglomerates is the increase of the particulate matter concentration. Traditional systems for particulate matter (PM) monitoring have a great number of drawbacks but the main issues are economical and are related to the installation costs and never ending periodical maintenance expenses. After all there are installations of such systems but their number is limited and having in mind the growth of population, cities and industry areas, there is even a bigger need for more information on air quality because PM changes non-linearly, has a wide range and different sources. In this paper, we propose an approach, based on low-cost sensor nodes, for real-time measuring and obtaining information about the PM concentration. The adoption of that approach allows for a detailed study of the intensities of pollution and its sources. The system power supply is powered by a PV module. The power supply unit is designed using a model-based design that is a new approach to prototyping power-operated electronic devices with guaranteed performance.
This paper presents an approach for implementing an automated hit detection and score calculation system for a steel dartboard using a standard webcam. First, the rectilinear field separations of the dartboard are described mathematically by means of line slopes and are than stored. These slopes serve as a basis for later score calculation. In addition, thrown darts have to be detected and the pixel at which the dart cuts the dartboard has to be determined. When this information is known, a comparison is made using the line slopes, allowing the field number of the hit to be detected. The decision for single, double or triple hit is made by evaluating the defined colors on the dartboard. All these functions are then packaged in a Matlab GUI.
The paper describes a systematic approach for a precise short-time cloud coverage prediction based on an optical system. We present a distinct pre-processing stage that uses a model based clear sky simulation to enhance the cloud segmentation in the images. The images are based on a sky imager system with fish-eye lens optic to cover a maximum area. After a calibration step, the image is rectified to enable linear prediction of cloud movement. In a subsequent step, the clear sky model is estimated on actual high dynamic range images and combined with a threshold based approach to segment clouds from sky. In the final stage, a multi hypothesis linear tracking framework estimates cloud movement, velocity and possible coverage of a given photovoltaic power station. We employ a Kalman filter framework that efficiently operates on the rectified images. The evaluation on real world data suggests high coverage prediction accuracy above 75%.
The fast and cost-effective manufacturing of tools for thermoforming is an essential requirement to shorten the development time of products. Thus, additive processes are used increasingly in tooling for thermoforming of plastic sheets. However, a disadvantage of many additive methods is that they are highly cost-intensive, since complex systems based on laser technology and expensive metal powders are needed. Therefore, this paper examines how to work with favorable additive methods, e.g. Binder Jetting, to manufacture tools, which provide sufficient strength for thermoforming. The use of comparatively low-priced inkjet technology for the layer construction and a polymer plaster as material can be expected to result in significant cost reductions. Based on a case study using a cowling (engine bonnet) for an Unmanned Aerial Vehicle (UAV), the development of a complex tool for thermoforming is demonstrated. The object in this study is to produce a tool for a complex-shaped component in small numbers and high quality in a short time and at reasonable costs. Within the tooling process, integrated vacuum channels are implemented in additive tooling without the need for additional post-processing (for example, drilling). In addition, special technical challenges, such as the demolding of undercuts or the parting of the tool are explained. All process steps from tool design to the use of the additively manufactured tool are analyzed. Based on the manufacturing of a small series of cowlings for a UAV made of plastic sheets (ABS), it is shown, that the Binder Jetting offers sufficient mechanical and thermal strength for additive tooling. In addition, an economic evaluation of the tool manufacturing and a detailed consideration of the required manufacturing times for the different process steps are carried out. Finally, a comparison is made with conventional and alternative additive methods of tooling.
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.
Narrowband IoT (NB-IoT) as a radio access technology for the cellular Internet of Things (cIoT) is getting more traction due to attractive system parameters, new proposals in the 3 rd Generation Partnership Project (3GPP) Release 14 for reduced power consumption and ongoing world-wide deployment. As per 3GPP, the low-power and wide-area use cases in 5G specification will be addressed by the early NB-IoT and Long-Term Evolution for Machines (LTE-M) based technologies. Since these cIoT networks will operate in a spatially distributed environment, there are various challenges to be addressed for tests and measurements of these networks. To meet these requirements, unified emulated and field testbeds for NB-IoT-networks were developed and used for extensive performance measurements. This paper analyses the results of these measurements with regard to RF coverage, signal quality, latency, and protocol consistency.
The monitoring of industrial environments ensures that highly automated processes run without interruption. However, even if the industrial machines themselves are monitored, the communication lines are currently not continuously monitored in todays installations. They are checked usually only during maintenance intervals or in case of error. In addition, the cables or connected machines usually have to be removed from the system for the duration of the test. To overcome these drawbacks, we have developed and implemented a cost-efficient and continuous signal monitoring of Ethernet-based industrial bus systems. Several methods have been developed to assess the quality of the cable. These methods can be classified to either passive or active. Active methods are not suitable if interruption of the communication is undesired. Passive methods, on the other hand, require oversampling, which calls for expensive hardware. In this paper, a novel passive method combined with undersampling targeting cost-efficient hardware is proposed.
Enabling ultra-low latency is one of the major drivers for the development of future cellular networks to support delay sensitive applications including factory automation, autonomous vehicles and tactile internet. Narrowband Internet of Things (NB-IoT) is a 3 rd Generation Partnership Project (3GPP) Release 13 standardized cellular network currently optimized for massive Machine Type Communication (mMTC). To reduce the latency in cellular networks, 3GPP has proposed some latency reduction techniques that include Semi Persistent Scheduling (SPS) and short Transmission Time Interval (sTTI). In this paper, we investigate the potential of adopting both techniques in NB-IoT networks and provide a comprehensive performance evaluation. We firstly analyze these techniques and then implement them in an open-source network simulator (NS3). Simulations are performed with a focus on Cat-NB1 User Equipment (UE) category to evaluate the uplink user-plane latency. Our results show that SPS and sTTI have the potential to greatly reduce the latency in NB-IoT systems. We believe that both techniques can be integrated into NB-IoT systems to position NB-IoT as a preferred technology for low data rate Ultra-Reliable Low-Latency Communication (URLLC) applications before 5G has been fully rolled out.
With the surge in global data consumption with proliferation of Internet of Things (IoT), remote monitoring and control is increasingly becoming popular with a wide range of applications from emergency response in remote regions to monitoring of environmental parameters. Mesh networks are being employed to alleviate a number of issues associated with single-hop communication such as low area coverage, reliability, range and high energy consumption. Low-power Wireless Personal Area Networks (LoWPANs) are being used to help realize and permeate the applicability of IoT. In this paper, we present the design and test of IEEE 802.15.4-compliant smart IoT nodes with multi-hop routing. We first discuss the features of the software stack and design choices in hardware that resulted in high RF output power and then present field test results of different baseline network topologies in both rural and urban settings to demonstrate the deployability and scalability of our solution.
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.
This article deals with the problem of wireless synchronization between onboard computing devices of small-sized unmanned aerial vehicles (SUAV) equipped with integrated wireless chips (IWC). Accurate synchronization between several devices requires the precise timestamping of batches transmitting and receiving on each of them. The best precision is demonstrated by those solutions where timestamping is performed on the PHY level, right after modulation/demodulation of the batch. Nowadays, most of the currently produced IWC are Systems-on-a-Chip (SoC) that include both PHY and MAC, implemented with one or several processor cores application. SoC allows create more cost and energy efficient wireless devices. At the same time, it limits the developers direct access to the internal signals and significantly complicates precise timestamping for sent and received batches, required for mutual synchronization of industrial devices. Some modern IEEE 802.11 IWCs have inbuilt functions that use internal chip clock to register timestamps. However, high jitter of the interfaces between the external device and IWC degrades the comparison of the timestamps from the internal clock to those registered by external devices. To solve this problem, the article proposes a novel approach to the synchronization, based on the analysis of IWC receiver input potential. The benefit of this approach is that there is no need to demodulate and decode the received batches, thus allowing it implementation with low-cost IWCs. In this araticle, Cypress CYW43438 was taken as an example for designing hardware and software solutions for synchronization between two SUAV onboard computing devices, equipped with IWC. The results of the performed experimental studies reveal that mutual synchronization error of the proposed method does not exceed 10 μs.
Low latency communication is essential to enable mission-critical machine-type communication (mMTC) use cases in cellular networks. Factory and process automation are major areas that require such low latency communication. In this paper, we investigate the potential of adopting the semi-persistent scheduling (SPS) latency reduction technique in narrowband LTE (NB-LTE) networks and provide a comprehensive performance evaluation. First, we investigate and implement SPS in an open-source network simulator (NS3). We perform simulations with a focus on LTE-M and Narrowband IoT (NB-IoT) systems and evaluate the impact of the SPS technique on the uplink latency of these narrowband systems in real industrial automation scenarios. The performance gain of adopting SPS is analyzed and the results is compared with the legacy dynamic scheduling. Our results show that SPS has the potential to reduce the latency of cellular Internet of Things (cIoT) networks. We believe that SPS can be integrated into LTE-M and NB-IoT systems to support low-latency industrial applications.
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.
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.
This paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use of the self-produced electricity. The benefit to the grid is from the reduced peaks in the PV feed-in and the grid power consumption. This would allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.
Printed electronics can benefit from the deployment of electrolytesas gate insulators,which enables a high gate capacitance per unit area (1–10 μFcm−2) due to the formation of electrical double layers (EDLs). Consequently, electrolyte-gated field-effect transistors (EGFETs) attain high-charge carrier densities already in the subvoltage regime, allowing for low-voltage operation of circuits and systems. This article presents a systematic study of lumped terminal capacitances of printed electrolyte-gated transistors under various dc bias conditions. We perform voltage-dependent impedancemeasurements and separate extrinsic components from the lumped terminal capacitance.
The proposed Meyer-like capacitance model, which also accounts for the nonquasi-static (NQS) effect, agrees well with experimental data. Finally, to verify the model, we implement it in Verilog-A and simulate the transient response of an inverter and a ring oscillator circuit. Simulation results are in good agreement with the measurement data of fabricated devices.
Printed systems spark immense interest in industry, and for several parts such as solar cells or radio frequency identification antennas, printed products are already available on the market. This has led to intense research; however, printed field-effect transistors (FETs) and logics derived thereof still have not been sufficiently developed to be adapted by industry. Among others, one of the reasons for this is the lack of control of the threshold voltage during production. In this work, we show an approach to adjust the threshold voltage (Vth) in printed electrolyte-gated FETs (EGFETs) with high accuracy by doping indium-oxide semiconducting channels with chromium. Despite high doping concentrations achieved by a wet chemical process during precursor ink preparation, good on/off-ratios of more than five orders of magnitude could be demonstrated. The synthesis process is simple, inexpensive, and easily scalable and leads to depletion-mode EGFETs, which are fully functional at operation potentials below 2 V and allows us to increase Vth by approximately 0.5 V.
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.
Printed electronics (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customization per application, even in small quantities due to low-cost printing compared with lithography. However, the personalized and on-demand fabrication, the non-standard circuit design, and the limited number of printing layers with larger geometries compared with traditional silicon chip manufacturing open doors for new and unique reverse engineering (RE) schemes for this technology. In this paper, we present a robust RE methodology based on supervised machine learning, starting from image acquisition all the way to netlist extraction. The results show that the proposed RE methodology can reverse engineer the PE circuits with very limited manual effort and is robust against non-standard circuit design, customized layouts, and high variations resulting from the inherent properties of PE manufacturing processes.
Printed electrolyte-gated oxide electronics is an emerging electronic technology in the low voltage regime (≤1 V). Whereas in the past mainly dielectrics have been used for gating the transistors, many recent approaches employ the advantages of solution processable, solid polymer electrolytes, or ion gels that provide high gate capacitances produced by a Helmholtz double layer, allowing for low-voltage operation. Herein, with special focus on work performed at KIT recent advances in building electronic circuits based on indium oxide, n-type electrolyte-gated field-effect transistors (EGFETs) are reviewed. When integrated into ring oscillator circuits a digital performance ranging from 250 Hz at 1 V up to 1 kHz is achieved. Sequential circuits such as memory cells are also demonstrated. More complex circuits are feasible but remain challenging also because of the high variability of the printed devices. However, the device inherent variability can be even exploited in security circuits such as physically unclonable functions (PUFs), which output a reliable and unique, device specific, digital response signal. As an overall advantage of the technology all the presented circuits can operate at very low supply voltages (0.6 V), which is crucial for low-power printed electronics applications.
Electrolyte-gated, printed field-effect transistors exhibit high charge carrier densities in the channel and thus high on-currents at low operating voltages, allowing for the low-power operation of such devices. This behavior is due to the high area-specific capacitance of the device, in which the electrolyte takes the role of the dielectric layer of classical architectures. In this paper, we investigate intrinsic double-layer capacitances of ink-jet printed electrolyte-gated inorganic field-effect transistors in both in-plane and top-gate architectures by means of voltage-dependent impedance spectroscopy. By comparison with deembedding structures, we separate the intrinsic properties of the double-layer capacitance at the transistor channel from parasitic effects and deduce accurate estimates for the double-layer capacitance based on an equivalent circuit fitting. Based on these results, we have performed simulations of the electrolyte cutoff frequency as a function of electrolyte and gate resistances, showing that the top-gate architecture has the potential to reach the kilohertz regime with proper optimization of materials and printing process. Our findings additionally enable accurate modeling of the frequency-dependent capacitance of electrolyte/ion gel-gated devices as required in the small-signal analysis in the circuit simulation.
Printed electronics (PE) is a fast growing technology with promising applications in wearables, smart sensors and smart cards since it provides mechanical flexibility, low-cost, on-demand and customizable fabrication. To secure the operation of these applications, True Random Number Generators (TRNGs) are required to generate unpredictable bits for cryptographic functions and padding. However, since the additive fabrication process of PE circuits results in high intrinsic variation due to the random dispersion of the printed inks on the substrate, constructing a printed TRNG is challenging. In this paper, we exploit the additive customizable fabrication feature of inkjet printing to design a TRNG based on electrolyte-gated field effect transistors (EGFETs). The proposed memory-based TRNG circuit can operate at low voltages (≤ 1 V ), it is hence suitable for low-power applications. We also propose a flow which tunes the printed resistors of the TRNG circuit to mitigate the overall process variation of the TRNG so that the generated bits are mostly based on the random noise in the circuit, providing a true random behaviour. The results show that the overall process variation of the TRNGs is mitigated by 110 times, and the simulated TRNGs pass the National Institute of Standards and Technology Statistical Test Suite.
Printed Electronics is perceived to have a major impact in the fields of smart sensors, Internet of Things and wearables. Especially low power printed technologies such as electrolyte gated field effect transistors (EGFETs) using solution-processed inorganic materials and inkjet printing are very promising in such application domains. In this paper, we discuss a modeling approach to describe the variations of printed devices. Incorporating these models and design flows into our previously developed printed design system allows for robust circuit design. Additionally, we propose a reliability-aware routing solution for printed electronics technology based on the technology constraints in printing crossovers. The proposed methodology was validated on multiple benchmark circuits and can be easily integrated with the design automation tools-set.
In the domain of printed electronics (PE), field-effect transistors (FETs) with an oxide semiconductor channel are very promising. In particular, the use of high gate-capacitance of the composite solid polymer electrolytes (CSPEs) as a gate-insulator ensures extremely low voltage requirements. Besides high gate capacitance, such CSPEs are proven to be easily printable, stable in air over wide temperature ranges, and possess high ion conductivity. These CSPEs can be sensitive to moisture, especially for high surface-to-volume ratio printed thin films. In this paper, we provide a comprehensive experimental study on the effect of humidity on CSPE-gated single transistors. At the circuit level, the performance of ring oscillators (ROs) has been compared for various humidity conditions. The experimental results of the electrolyte-gated FETs (EGFETs) demonstrate rather comparable currents between 30%-90% humidity levels. However, the shifted transistor parameters lead to a significant performance change of the RO frequency behavior. The study in this paper shows the need of an impermeable encapsulation for the CSPE-gated FETs to ensure identical performance at all humidity conditions.
Smart Home or Smart Building applications are a growing market. An increasing challenge is to design energy efficient Smart Home applications to achieve sustainable and green homes. Using the example of the development of an Indoor Smart Gardening system with wireless monitoring and automated watering this paper is discussing in particular the design issue of energy autonomous working sensors and actuators for home automation. Most important part of the presented Smart Gardening system is a 3D printed smart flower pot for single plants. The smart flower pot has integrated a water reservoir for automated plant irrigation and an electronic for monitoring important plant parameters and the water level of the water reservoir. Energy harvesting with solar cells enables energy autonomous working of the flower pot. A low-power wireless interface also integrated in the flowerpot and an external gateway based on a Raspberry Pi 3 enables wireless networking of multiple of those flower pots. The gateway is used for evaluating the plant parameters and as a user interface. Particularly the architecture of the energy autonomous wireless flower pot will be considered, because fully energy autonomous sensors and actuators for home automation could not be implemented without special concepts for the energy supply and the overall electronic.
Radio frequency identification (RFID) antennas are popular for high frequency (HF) RFID, energy transfer and near field communication (NFC) applications. Particularly for wireless measurement systems the RFID/NFC technology is a good option to implement a wireless communication interface. In this context, the design of corresponding reader and transmitter antennas plays a major role for achieving suitable transmission quality. This work proves the feasibility of the rapid prototyping of a RFID/NFC antenna, which is used for the wireless communication and energy harvesting at the required frequency of 13.56 MHz. A novel and low-cost direct ink writing (DIW) technology utilizing highly viscous silver nanoparticle ink is used for this process. This paper describes the development and analysis of low-cost printed flexible RFID/NFC antennas on cost-effective substrates for a microelectronic vital parameter measurement system. Furthermore, we compare the measured technical parameters with existing copper-based counterparts on a FR4 substrate.
Smart Home-/Smart-Building-Anwendungen sind ein stetig wachsender Markt. Smart Gardening ist ein Beispiel dafür, Nutzern mehr Komfort und eine bessere Lebensqualität zu Hause oder in Bürogebäuden zu ermöglichen. Im Rahmen dieses Beitrags wird die Entwicklung eines Indoor-Smart-Gardening-Systems mit dem Fokus auf energieautarkes Arbeiten vorgestellt. Herzstück des Systems ist ein 3D-gedruckter Blumentopf für einzelne Pflanzen mit integrierter Elektronik zum Monitoring der wichtigsten Pflanzenparameter und einem integrierten Wasserreservoir mit Tauchpumpe für das automatisierte Bewässern der Pflanze. Energy Harvesting per Solarzellen ermöglicht ein energieautarkes Arbeiten des Blumentopfes. Eine selbstentwickelte Low-Power-Funkschnittstelle im Blumentopf und ein externes Gateway ermöglichen die drahtlose Vernetzung mehrerer Pflanzen. Das Gateway dient zur Auswertung der Pflanzenparameter, der Ansteuerung der im Netzwerk vorhandenen Blumentöpfe und als Benutzerinterface.
Kleinstlebewesen vorgestellt, das Vitalparameter erfasst und diese in einem FRAM-Speicher bis zum Auslesen abspeichert. Durch eine drahtlose RFID-/NFC-Ausleseschnittstelle kann die erfasste Körpertemperatur und der Puls der letzten Wochen ausgelesen werden. Alle Einstellungen des Messsystems können durch einen geeigneten RFID-Reader für Laptops oder durch Smartphones über die NFC-Schnittstelle geändert werden. Das vollständige Aufladen des nur 3 g leichten und 15 mm x 25 mm großen Messsystems erfolgt durch eine selbstgedruckte RFID-Reader-Antenne in Verbindung mit einem RFID-Reader und benötigt hierzu weniger als 21 Stunden. Bei vollständig aufgeladenem Energiespeicher ist ein Betrieb von 47 Tagen möglich. Dies wird durch ein speziell für das Messsystem konzipiertes Lade- und Powermanagement erreicht. Neben der Auswahl von energiesparenden Komponenten für die Hardware und deren bestmöglichen Nutzung, wurde die Software so optimiert, dass das Programm schnell und stromsparend abgearbeitet wird. Die Erweiterbarkeit und Anpassung wird durch das modulare Konzept auch in anderen Bereichen gewährleistet.
The high peak power in comparison to the average transmit power is one of the major long-standing problems in multicarrier modulation and is known as the PAPR (peak to average power ratio) problem. Many PAPR reduction methods have been devised and their comparison is usually based on the complementary cumulative distribution function (CCDF) of the PAPR. While this comparison is straightforward and easy to compute, its relationship with system performance metrics like the (uncoded) BER or the word error rate (WER) for coded systems is considerably more involved. We evaluate the impact of the PAPR on performance metrics like uncoded BER, EVM (error vector magnitude), mutual information and the WER for soft decoding. In this context, we find that system performance is not necessarily degraded by an increasing PAPR. We show that a high number of subcarriers, despite the corresponding high PAPR, is actually not a problem for the system performance and provide a simple explanation for this seemingly counter-intuitive fact.
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.
Dissertation D. Dongol
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 and emergency vehicle lighting. We show that with recent deep learning networks we are 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, stop lines and even complete crossings. Best results are achieved using Faster R-CNN with Inception v2 showing an overall accuracy of 0.84 at 7 Hz.
Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic selection algorithms have been introduced to overcome tedious manual (try and error) tuning of these parameters. Due to its very high sample efficiency, Bayesian Optimization over a Gaussian Processes modeling of the parameter space has become the method of choice. Unfortunately, this approach suffers from a cubic compute complexity due to underlying Cholesky factorization, which makes it very hard to be scaled beyond a small number of sampling steps. In this paper, we present a novel, highly accurate approximation of the underlying Gaussian Process. Reducing its computational complexity from cubic to quadratic allows an efficient strong scaling of Bayesian Optimization while outperforming the previous approach regarding optimization accuracy. First experiments show speedups of a factor of 162 in single node and further speed up by a factor of 5 in a parallel environment.
Current training methods for deep neural networks boil down to very high dimensional and non-convex optimization problems which are usually solved by a wide range of stochastic gradient descent methods. While these approaches tend to work in practice, there are still many gaps in the theoretical understanding of key aspects like convergence and generalization guarantees, which are induced by the properties of the optimization surface (loss landscape). In order to gain deeper insights, a number of recent publications proposed methods to visualize and analyze the otimization surfaces. However, the computational cost of these methods are very high, making it hardly possible to use them on larger networks. In this paper, we present the GradVis Toolbox, an open source library for efficient and scalable visualization and analysis of deep neural network loss landscapes in Tesorflow and PyTorch. Introducing more efficient mathematical formulations and a novel parallelization scheme, GradVis allows to plot 2d and 3d projections of optimization surfaces and trajectories, as well as high resolution second order gradient information for large networks.
Recent deep learning based approaches have shown remarkable success on object segmentation tasks. However, there is still room for further improvement. Inspired by generative adversarial networks, we present a generic end-to-end adversarial approach, which can be combined with a wide range of existing semantic segmentation networks to improve their segmentation performance. The key element of our method is to replace the commonly used binary adversarial loss with a high resolution pixel-wise loss. In addition, we train our generator employing stochastic weight averaging fashion, which further enhances the predicted output label maps leading to state-of-the-art results. We show, that this combination of pixel-wise adversarial training and weight averaging leads to significant and consistent gains in segmentation performance, compared to the baseline models.
Deep generative models have recently achieved impressive results for many real-world applications, successfully generating high-resolution and diverse samples from complex datasets. Due to this improvement, fake digital contents have proliferated growing concern and spreading distrust in image content, leading to an urgent need for automated ways to detect these AI-generated fake images.
Despite the fact that many face editing algorithms seem to produce realistic human faces, upon closer examination, they do exhibit artifacts in certain domains which are often hidden to the naked eye. In this work, we present a simple way to detect such fake face images - so-called DeepFakes. Our method is based on a classical frequency domain analysis followed by basic classifier. Compared to previous systems, which need to be fed with large amounts of labeled data, our approach showed very good results using only a few annotated training samples and even achieved good accuracies in fully unsupervised scenarios. For the evaluation on high resolution face images, we combined several public datasets of real and fake faces into a new benchmark: Faces-HQ. Given such high-resolution images, our approach reaches a perfect classification accuracy of 100% when it is trained on as little as 20 annotated samples. In a second experiment, in the evaluation of the medium-resolution images of the CelebA dataset, our method achieves 100% accuracy supervised and 96% in an unsupervised setting. Finally, evaluating a low-resolution video sequences of the FaceForensics++ dataset, our method achieves 91% accuracy detecting manipulated videos.
Recent studies have shown remarkable success in image-to-image translation for attribute transfer applications. However, most of existing approaches are based on deep learning and require an abundant amount of labeled data to produce good results, therefore limiting their applicability. In the same vein, recent advances in meta-learning have led to successful implementations with limited available data, allowing so-called few-shot learning.
In this paper, we address this limitation of supervised methods, by proposing a novel approach based on GANs. These are trained in a meta-training manner, which allows them to perform image-to-image translations using just a few labeled samples from a new target class. This work empirically demonstrates the potential of training a GAN for few shot image-to-image translation on hair color attribute synthesis tasks, opening the door to further research on generative transfer learning.
Machine Learning als Schlüsseltechnologie für Digitalisierung: Wie funktioniert maschinelles Lernen?
(2019)
Apache Hadoop is a well-known open-source framework for storing and processing huge amounts of data. This paper shows the usage of the framework within a project of the university in cooperation with a semiconductor company. The goal of this project was to supplement the existing data landscape by the facilities of storing and analyzing the data on a new Apache Hadoop based platform.