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A Gamified and Adaptive Learning System for Neurodivergent Workers in Electronic Assembling Tasks
(2020)
Learning and work-oriented assistive systems are often designed to fit the workflow of neurotypical workers. Neurodivergent workers and individuals with learning disabilities often present cognitive and sensorimotor characteristics that are better accommodated with personalized learning and working processes. Therefore, we designed an adaptive learning system that combines an augmented interaction space with user-sensitive virtual assistance to support step-by-step guidance for neurodivergent workers in electronic assembling tasks. Gamified learning elements were also included in the interface to provide self-motivation and praise whenever users progress in their learning and work achievements.
In this work a method for the estimation of current slopes induced by inverters operating interior permanent magnet synchronous machines is presented. After the derivation of the estimation algorithm, the requirements for a suitable sensor setup in terms of accuracy, dynamic and electromagnetic interference are discussed. The boundary conditions for the estimation algorithm are presented with respect to application within high power traction systems. The estimation algorithm is implemented on a field programmable gateway array. This moving least-square algorithm offers the advantage that it is not dependent on vectors and therefore not every measured value has to be stored. The summation of all measured values leads to a significant reduction of the required storage units and thus decreases the hardware requirements. The algorithm is designed to be calculated within the dead time of the inverter. Appropriate countermeasures for disturbances and hardware restrictions are implemented. The results are discussed afterwards.
This paper presents a novel low-jitter interface between a low-cost integrated IEEE802.11 chip and a FPGA. It is designed to be part of system hardware for ultra-precise synchronization between wireless stations. On physical level, it uses Wi-Fi chip coexistence signal lines and UART frame encoding. On its basis, we propose an efficient communication protocol providing precise timestamping of incoming frames and internal diagnostic mechanisms for detecting communication faults. Meanwhile it is simple enough to be implemented both in low-cost FPGA and commodity IEEE802.11 chip firmware. The results of computer simulation shows that developed FPGA implementation of the proposed protocol can precisely timestamp incoming frames as well as detect most of communication errors even in conditions of high interference. The probability of undetected errors was investigated. The results of this analysis are significant for the development of novel wireless synchronization hardware.
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.
Wireless communication technologies play a major role to enable megatrends like Internet of Things (IoT) and Industry 4.0. The Narrowband Wireless WAN (NBWWAN) introduced to meet the long range and low power requirements of spatially distributed wireless communication use cases. These networks introduce additional challenges in testing because the network topology and RF characteristics become particularly complex and thus a multitude of different scenarios must be tested. This paper describes the infrastructure for automated testing of radio communication and for systematic measurements of the network performance of NBWWAN.
Analysis of Amplitude and Phase Errors in Digital-Beamforming Radars for Automotive Applications
(2020)
Fundamentally, automotive radar sensors with Digital-Beamforming (DBF) use several transmitter and receiver antennas to measure the direction of the target. However, hardware imperfections, tolerances in the feeding lines of the antennas, coupling effects as well as temperature changes and ageing will cause amplitude and phase errors. These errors can lead to misinterpretation of the data and result in hazardous actions of the autonomous system. First, the impact of amplitude and phase errors on angular estimation is discussed and analyzed by simulations. The results are compared with the measured errors of a real radar sensor. Further, a calibration method is implemented and evaluated by measurements.
The TriRhenaTech alliance presents a collection of accepted papers of the cancelled tri-national 'Upper-Rhine Artificial Intelligence Symposium' planned for 13th May 2020 in Karlsruhe. The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, and Offenburg, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes écoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.
Astronomical phenomena fascinate people from the very beginning of mankind up to today. In this paper the authors will present their experience with photography of astronomical events. The main focus will be on aurora borealis, comet Neowise, total lunar eclipses and how mobile devices open up new possibilities to observe the green flash. Our efforts were motivated by the great impact and high number of viewers of these events. Visitors from over a hundred countries watched our live broadcasts.
Furthermore, we report on our experiences with the photography of optical phenomena such as polar lights Fig. 1, comet Neowise with a Delta Aquariids meteor Fig. 11, and lunar eclipses Fig. 12.
Bei dem vorgestellten Ansatz soll der Auftreffpunkt des Pfeils durch die Kreuzkorrelation von Audio-Signalen bestimmt werden. Das Auftreffen des Pfeils erzeugt ein charakteristisches Geräusch, welches von mehreren Mikrofonen in bestimmter Anordnung um die Dartscheibe herum in elektrische Signale umgewandelt wird. Mithilfe der Schallgeschwindigkeit und den Zeitdifferenzen, welche die Schallwelle zu den einzelnen Mikrofonen benötigt soll dann der Auftreffpunkt berechnet werden.
The interaction between agents in multiagent-based control systems requires peer to peer communication between agents avoiding central control. The sensor nodes represent agents and produce measurement data every time step. The nodes exchange time series data by using the peer to peer network in order to calculate an aggregation function for solving a problem cooperatively. We investigate the aggregation process of averaging data for time series data of nodes in a peer to peer network by using the grouping algorithm of Cichon et al. 2018. Nodes communicate whether data is new and map data values according to their sizes into a histogram. This map message consists of the subintervals and vectors for estimating the node joining and leaving the subinterval. At each time step, the nodes communicate with each other in synchronous rounds to exchange map messages until the network converges to a common map message. The node calculates the average value of time series data produced by all nodes in the network by using the histogram algorithm. The relative error for comparing the output of averaging time series data, and the ground truth of the average value in the network will decrease as the size of the network increases. We perform simulations which show that the approximate histograms method provides a reasonable approximation of time series data.
Do you know that for each banana bunch the complete plant must be cut as well? Only in Brazil 440 million trees are planted annually. With an average weight of 30 kg per banana plant you can estimate about 13,5 million tons of banana residues per year. Although there exist some projects to use these residues for the production of valuable products (e.g fibers for textile and paper production) most of this organic waste material is unused and left for composting on the farmland.
The basic idea of this project is to evaluate this organic waste material for converting it to a renewable and CO2 neutral fuel. Therefore, the different parts of the banana plant (heart, leaves and pseudo stem) were analyzed regarding their biogas potential (specific biogas yield and biogas production kinetics). In further studies the effect of mechanical and enzymatic pretreatments of the different parts of the plants was investigated. This examination could then be the basis for an energetic usage of this organic residue.
The biogas batch experiments were performed according to the german guideline VDI 4630 in 2-L-Batch reactors at 37°C. As biogas substrates, the heart, the leaves and the pseudo stem of the banana plant residue with and without enzymatic/mechanical pretreatment were used.
The different parts of the banana plants result in a specific biogas production yield in the range of 260-470 norm liters per kg organic dry mass.
To determine the influence of the mechanical pretreatment (particle size 1-15 mm) on the biogas production kinetics, the kinetic constants were defined and calculated. The reduction of the particle size leads to an improved biogas production kinetics. Therefore experiments will demonstrate, if the results from the batch experiments can be converted in the continuous fed biogas reactor. The experiments of the enzymatic pretreatment are still under investigation.
Efficient collaborative robotic applications need a combination of speed and separation monitoring, and power and force limiting operations. While most collaborative robots have built-in sensors for power and force limiting operations, there are none with built-in sensor systems for speed and separation monitoring. This paper proposes a system for speed and separation monitoring directly from the gripper of the robot. It can monitor separation distances of up to three meters. We used single-pixel Time-of-Flight sensors to measure the separation distance between the gripper and the next obstacle perpendicular to it. This is the first system capable of measuring separation distances of up to three meters directly from the robot's gripper.
Well-designed and informative product presentations can support consumers in making purchase decisions. There are plenty of facts and details about a product of interest. However, also emotions are an important aspect for the purchase decision. The unique visualization opportunities of virtual reality (VR) can give users of VR applications the feeling of being there (telepresence). The applications can intensely engage them in a flow experience, comprising the four dimensions of enjoyment, curiosity, focused attention and control. In this work, we claim that VR product presentations can create subjective product experiences for consumers and motivate them to reuse this innovative type of product presentation in the future, by immersing them in a virtual world and causing them to interact with it. To verify the conceptual model a study was conducted with 551 participants who explored a VR hotel application. The results indicate that VR product presentations evoke positive emotions among consumers. The virtual experience made potential customers focus their attention on the virtual world and aroused their curiosity about getting more information about the product in an enjoyable way. In contrast to the theoretical assumption, control did not influence the users’ behavioral intentions to reuse VR product presentation. We conclude that VR product presentations create a feeling of telepresence, which leads to a flow experience that contributes to the behavioral intention of users to reuse VR product presentations in the future.
Co-Designing Assistive Tools to Support Social Interactions by Individuals Living with Deafblindness
(2020)
Deafblindness is a dual sensory impairment that affects many aspects of life, including mobility, access to information, communication, and social interactions. Furthermore, individuals living with deafblindness are under a high risk of social isolation. Therefore, we identified opportunities for applying assistive tools to support social interactions through co-ideation activities with members of the deafblind community. This work presents our co-design approach, lessons learned and directions for designing meaningful assistive tools for dual sensory loss.
Time Sensitive Networking (TSN) provides mechanisms to enable deterministic and real-time networking in industrial networks. Configuration of these mechanisms is key to fully deploy and integrate TSN in the networks. The IEEE 802.1 Qcc standard has proposed different configuration models to implement a TSN configuration. Up until now, TSN and its configuration have been explored mostly for Ethernet-based industrial networks. However, they are still considered “work-in-progress” for wireless networks. This work focuses on the fully centralized model and describes a generic concept to enable the configuration of TSN mechanisms in wireless industrial networks. To this end, a configuration entity is implemented to conFigure the wireless end stations to satisfy their requirements. The proposed solution is then validated with the Digital Enhanced Cordless Telecommunication ultra-low energy (DECT ULE) wireless communication protocol.
Laser ultrasound was used to determine dispersion curves of surface acoustic waves on a Si (001) surface covered by AlScN films with a scandium content between 0 and 41%. By including off-symmetry directions for wavevectors, all five independent elastic constants of the film were extracted from the measurements. Results for their dependence on the Sc content are presented and compared to corresponding data in the literature, obtained by alternative experimental methods or by ab-initio calculations.
Cross-industry innovation is commonly understood as identification of analogies and interdisciplinary transfer or copying of technologies, processes, technical solutions, working principles or models between industrial sectors. In general, creative thinking in analogies belongs to the efficient ideation techniques. However, engineering graduates and specialists frequently lack the skills to think across the industry boundaries systematically. To overcome this drawback an easy-to-use method based on five analogies has been evaluated through its applications by students and engineers in numerous experiments and industrial case studies. The proposed analogies help to identify and resolve engineering contradictions and apply approaches of the Theory of Inventive Problem Solving TRIZ and biomimetics. The paper analyses the outcomes of the systematized analogies-based ideation and outlines that its performance continuously grows with the engineering experience. It defines metrics for ideation efficiency and ideation performance function.
Die angestrebten Klimaschutzziele erfordern, dass Erneuerbare Energien längerfristig zur Hauptenergiequelle der Energieversorgung werden. Um dieses ehrgeizige Ziel zu erreichen, ist es angebracht konventionelle und erneuerbare Energie oder noch besser nachhaltige Einzelprozesse intelligent miteinander zu verknüpfen.
Das Projekt EBIPREP wird von einer interdisziplinären Forschergruppe bestehend aus Chemikern, Prozessingenieuren und Bioprozessingenieuren sowie Physikern, die auf Sensoren und Prozesssteuerung spezialisiert sind durchgeführt. Das Ziel ist es, neue Lösungen für die Nutzungswege von Holzhackschnitzeln und den bei der mechanischen Trocknung anfallenden Holzpresssaft zu entwickeln. Neben der Hackschnitzelvergasung und der katalytischen Reinigung des Holzgases steht die Nutzung des Holzpresssafts in Biogasanlagen und bei der biotechnologischen Wertstofferzeugung, z.B. bei der Enzymherstellung, im Vordergrund.
Was wir tun?
Das EBIPREP-Projekt wird von einer interdisziplinären Forschungsgruppe durchgeführt, die sich aus Chemikern, Prozessingenieuren, Bioprozessingenieuren und Physikern zusammensetzt. Ziel ist es, neue Lösungen für den Einsatz von Hackschnitzeln und Holzpresssaft zu entwickeln, die durch ein innovatives mechanisches Trocknungsverfahren gewonnen werden. Neben der Holzvergasung und katalytischen Reinigung des Holzgases ist der Einsatz von Holzpresssaft in Biogasanlagen und in biotechnologischen Produktionsprozessen von Wertstoffen vorgesehen. Holzhackschnitzel werden thermisch vergast. Es werden Online-Sensoren entwickelt, um die relevanten Parameter der stabilisierten und optimierten Einzelprozesse auszuwerten. Die Verknüpfung von thermischen und biotechnologischer Konversionsprozessen könnte dazu beitragen, die Dimension von Biogasreaktoren erheblich zu reduzieren. Diese Tatsache wird folglich zu einer spürbaren Kostensenkung führen.
Ziele des EBIPREP-Projekts
• die Vorteile der thermischen und biologischen Umwandlung von Biomasse zu kombinieren;
• Entwicklung eines Verfahrens zur Reduzierung von Schadstoffemissionen mit innovativen Sensoren und katalytische Behandlung von Synthesegasen;
• nachhaltige Produktion biotechnologischer wertvoller Produkte
• wirtschaftliche und ökologische Analyse des Gesamtprozesses im Vergleich zu den Einzelprozessen
• Einsatz von Prozessabwässern zur Erzeugung regenerativer Energie oder biotechnologischer Wertstoffe
• Erwerb neuer Kenntnisse auf dem Gebiet der Rückgewinnungstechnik von Rückständen
• und Energieerzeugung;
• Erweiterung neuer Anwendungsfelder für innovative Sensoren und Keramik
• Schäume für Katalysatoren;
• Senkung der Kosten für die Biogasproduktion
Im geplanten Übersichtsvortrag werden die vernetzten Strukturen des Projekts EBIPREP und deren zentralen Ergebnisse vorgestellt.
Background: A disturbed synchronization of the ventricular contraction can cause a highly developed systolic heart failure in affected patients, which can often be explained by a diseased left bundle branch block (LBBB). If medication remains unresponsive, the concerned patients will be treated with a cardiac resynchronization therapy (CRT) system. The aim of this study was to integrate His bundle pacing into the Offenburg heart rhythm model in order to visualize the electrical pacing field generated by His bundle pacing.
Methods: Modelling and electrical field simulation activities were performed with the software CST (Computer Simulation Technology) from Dessault Systèms. CRT with biventricular pacing is to be achieved by an apical right ventricular electrode and an additional left ventricular electrode, which is floated into the coronary vein sinus. This conventional type of biventricular pacing leads to a reduction of the left ventricular ejection fraction. Furthermore, the non-responder rate of the CRT therapy is about one third of the CRT patients.
Results: His bundle pacing represents a physiological alternative to conventional cardiac pacing and cardiac resynchronization. An electrode implanted in the His bundle emits a stronger electrical pacing field than the electrical pacing field of conventional cardiac pacemakers. The pacing of the His bundle was performed by the Medtronic Select Secure 3830 electrode with pacing voltage amplitudes of 3 V, 2 V and 1.5 V in combination with a pacing pulse duration of 1 ms.
Conclusions: Compared to conventional cardiac pacemaker pacing, His bundle pacing is capable of bridging LBBB conduction disorders in the left ventricle. The His bundle pacing electrical field is able to spread via the physiological pathway in the right and left ventricles for CRT with a narrow QRS-complex in the surface ECG.
The precise positioning of mobile systems is a prerequisite for any autonomous behavior, in an industrial environment as well as for field robotics. The paper describes the set up for an experimental platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. Two approaches are compared. First, a local method based on point cloud matching and integration of inertial measurement units is evaluated. Subsequent matching makes it possible to create a three-dimensional point cloud that can be used as a map in subsequent runs. The second approach is a full SLAM algorithm, based on graph relaxation models, incorporating the full sensor suite of odometry, inertial sensors, and 3D laser scan data.
Nowadays, the wide majority of Europeans uses smartphones. However, touch displays are still not accessible by everyone. Individuals with deafblindness, for example, often face difculties in accessing vision-based touchscreens. Moreover, they typically have few fnancial resources which increases the need for customizable, low-cost assistive devices. In this work-in-progress, we present four prototypes made from low-cost, every-day materials, that make modern pattern lock mechanisms more accessible to individuals with vision impairments or even with deafblindness. Two out of four prototypes turned out to be functional tactile overlays for accessing digital 4-by-4 grids that are regularly used to encode dynamic dot patterns. In future work, we will conduct a user study investigating whether these two prototypes can make dot-based pattern lock mechanisms more accessible for individuals with visual impairments or deafblindness.
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.
Wireless synchronization of industrial controllers is a challenging task in environments where wired solutions are not practical. The best solutions proposed so far to solve this problem require pretty expensive and highly specialized FPGA-based devices. With this work we counter the trend by introducing a straightforward approach to synchronize a fairly cheap IEEE 802.11 integrated wireless chip (IWC) with external devices. More specifically we demonstrate how we can reprogram the software running in the 802.11 IWC of the Raspberry Pi 3B and transform the receiver input potential of the wireless transceiver into a triggering signal for an external inexpensive FPGA. Experimental results show a mean-square synchronization error of less than 496 ns, while the absolute synchronization error does not exceed 6 μs. The jitter of the output signal that we obtain after synchronizing the clock of the external device did not exceed 5.2 μs throughout the whole measurement campaign. Even though we do not score new records in term of accuracy, we do in terms of complexity, cost, and availability of the required components: all these factors make the proposed technique a very promising of the deployment of large-scale low-cost automation solutions.
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.
During the day-to-day exploitation of localization systems in mines, the technical staff tends to incorrectly rearrange radio equipment: positions of devices may not be accurately marked on a map or their positions may not correspond to the truth. This situation may lead to positioning inaccuracies and errors in the operation of the localization system.This paper presents two Bayesian algorithms for the automatic corrections of positions of the equipment on the map using trajectories restored by the inertial measurement units mounted to mobile objects, like pedestrians and vehicles. As a basis, a predefined map of the mine represented as undirected weighted graph was used as input. The algorithms were implemented using the Simultaneous Localization and Mapping (SLAM) approach.The results prove that both methods are capable to detect misplacement of access points and to provide corresponding corrections. The discrete Bayesian filter outperforms the unscented Kalman filter, which, however, requires more computational power.
Deafblindness, a form of dual sensory impairment, signifcantly impacts communication, access to information and mobility. Inde- pendent navigation and wayfnding are main challenges faced by individuals living with combined hearing and visual impairments. We developed a haptic wearable that provides sensory substitution and navigational cues for users with deafblindness by conveying vibrotactile signals onto the body. Vibrotactile signals on the waist area convey directional and proximity information collected via a fisheye camera attached to the garment, while semantic informa- tion is provided with a tapping system on the shoulders. A playful scenario called “Keep Your Distance” was designed to test the navigation system: individuals with deafblindness were “secret agents” that needed to follow a “suspect”, but they should keep an opti- mal distance of 1.5 meters from the other person to win the game. Preliminary fndings suggest that individuals with deafblindness enjoyed the experience and were generally able to follow the directional cues.
Environmentally-friendly implementation of new technologies and eco-innovative solutions often faces additional secondary ecological problems. On the other hand, existing biological systems show a lesser environmental impact as compared to the human-made products or technologies. The paper defines a research agenda for identification of underlying eco-inventive principles used in the natural systems created through evolution. Finally, the paper proposes a comprehensive method for capturing eco-innovation principles in biological systems in addition and complementary to the existing biomimetic methods and TRIZ methodology and illustrates it with an example.
In this work, we evaluate two different image clustering objectives, k-means clustering and correlation clustering, in the context of Triplet Loss induced feature space embeddings. Specifically, we train a convolutional neural network to learn discriminative features by optimizing two popular versions of the Triplet Loss in order to study their clustering properties under the assumption of noisy labels. Additionally, we propose a new, simple Triplet Loss formulation, which shows desirable properties with respect to formal clustering objectives and outperforms the existing methods. We evaluate all three Triplet loss formulations for K-means and correlation clustering on the CIFAR-10 image classification dataset.
Learning to Walk With Toes
(2020)
This paper explains how a model-free (with respect to the robot model and the behavior to learn) approach can facilitate learning to walk from scratch. It is applied to a simulated Nao robot with toes. Results show an improvement of 30% in speed compared to a model without toes and also compared to our model-based approach, but with less stability.
Live streaming of events over an IP network as a catalyst in media technology education and training
(2020)
The paper describes how students are involved in applied research when setting up the technology and running a live event. Real-time IP transmission in broadcast environments via fiber optics will become increasingly important in the future. Therefore, it is necessary to create a platform in this area where students can learn how to handle IP infrastructure and fiber optics. With this in mind, we have built a fully functional TV control room that is completely IP-based. The authors present the steps in the development of the project and show the advantages of the proposed digital solutions. The IP network proves to be a synergy between the involved teams: participants of the robot competition and the members of the media team. These results are presented in the paper. Our activities aim to awaken enthusiasm for research and technology in young people. Broadcasts of live events are a good opportunity for "hands on" activities.
Threat Modelling is an accepted technique to identify general threats as early as possible in the software development lifecycle. Previous work of ours did present an open-source framework and web-based tool (OVVL) for automating threat analysis on software architectures using STRIDE. However, one open problem is that available threat catalogues are either too general or proprietary with respect to a certain domain (e.g. .Net). Another problem is that a threat analyst should not only be presented (repeatedly) with a list of all possible threats, but already with some automated support for prioritizing these. This paper presents an approach to dynamically generate individual threat catalogues on basis of the established CWE as well as related CVE databases. Roughly 60% of this threat catalogue generation can be done by identifying and matching certain key values. To map the remaining 40% of our data (~50.000 CVE entries) we train a text classification model by using the already mapped 60% of our dataset to perform a supervised machine-learning based text classification. The generated entire dataset allows us to identify possible threats for each individual architectural element and automatically provide an initial prioritization. Our dataset as well as a supporting Jupyter notebook are openly available.
Modeling of Random Variations in a Switched Capacitor Circuit based Physically Unclonable Function
(2020)
The Internet of Things (IoT) is expanding to a wide range of fields such as home automation, agriculture, environmental monitoring, industrial applications, and many more. Securing tens of billions of interconnected devices in the near future will be one of the biggest challenges. IoT devices are often constrained in terms of computational performance, area, and power, which demand lightweight security solutions. In this context, hardware-intrinsic security, particularly physically unclonable functions (PUFs), can provide lightweight identification and authentication for such devices. In this paper, random capacitor variations in a switched capacitor PUF circuit are used as a source of entropy to generate unique security keys. Furthermore, a mathematical model based on the ordinary least square method is developed to describe the relationship between random variations in capacitors and the resulting output voltages. The model is used to filter out systematic variations in circuit components to improve the quality of the extracted secrets.
Partial substitution of Al atoms with Sc in wurtzite AlN crystals increases the piezoelectric constants. This leads to an increased electromechanical coupling, which is required for high bandwidths in piezo-acoustic filters. The crystal bonds in Ah-xScxN (AlScN) are softened as function of Sc atomic percentage x, leading to reduction of phase velocity in the film. Combining high Sc content AlScN films with high velocity substrates favors higher order guided surface acoustic wave (SAW) modes [1]. This study investigates higher order SAW modes in epitaxial AlScN on sapphire (Al2O3). Their dispersion for Pt metallized epitaxial AlScN films on Al2O3was computed for two different propagation directions. Computed phase velocity dispersion branches were experimentally verified by the characterization of fabricated SAW resonators. The results indicated four wave modes for the propagation direction (0°, 0°, 0°), featuring 3D polarized displacement fields. The sensitivity of the wave modes to the elastic constants of AlScN was investigated. It was shown that due to the 3D polarization of the waves, all elastic constants have an influence on the phase velocity and can be measured by suitable weighting functions in material constant extraction procedures.
Im Rahmen des Forschungsprojekts Professional UX entwickelt die Hochschule Offenburg gemeinsam mit dem Softwarehaus Dr. Hornecker in Freiburg eine innovative Systemlösung, die es ermöglicht, anhand von Mimik, Stimme und Blickverlauf beim Nutzer entstehende Emotionen bei der Nutzung interaktiver Anwendungen zu erfassen und zu interpretieren. Ziel der Untersuchung ist es, Indikatoren zu identifizieren, die eine exakte Zuordnung von wahrgenommenen Reizen zu den jeweils ausgelösten Emotionen erlauben. Sobald negative Emotionen wie Ärger oder Unsicherheit auftreten, kann dieser erfasst und im Nachgang der jeweils irritierende Reiz eliminiert werden. Das Projektteam hat einen ersten Prototyp für die Professional UX Systemlösung in Form von Hard- und Software entwickelt, mit dem es möglich ist, UX-Messungen während der User Interaktion durchzuführen und automatisiert mithilfe von KI auswerten zu lassen.
Als Einstieg in den Diskurs über zivile Netzwerktechnologien, mobile Geräte, Onlinedienste und die Frage, wie sich die „Kirche der Zukunft“ (zumindest aus medienwissenschaftlicher Sicht) positionieren kann, dienen drei Zitate. Die Gegenüberstellung der darin vertretenen Positionen soll den Nutzen und die Folgen der zunehmend vollständigen Durchdringung (fast) aller Lebensbereiche mit Digitaltechnik für den Einzelnen wie für die Gesellschaft aufzeigen.
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 PHOTOPUR project aims to develop a photocatalytic process as a type of AOPs (Advanced Oxidation Processes) for the elimination of plant protection products (PPP) of the cleaning water used to wash sprayers. At INES a PV based energy supply for the photocatalytic cleaning system was developed within the framework of two bachelor theses and assembled as a demonstration unit. Then the system was step by step extended with further process automation features and pushed to a remote operating device. The final system is now available as a mobile unit mounted on a lab table. The latest step was the photocatalytic reactor module which completed the first PHOTOPUR prototype. The system is actually undergoing an intensive testing phase with performance checks at the consortium partners. First results give an overview about the successful operation.
Interaction and capturing information from the surrounding is dominated by vision and hearing. Haptics on the other side, widens the bandwidth and could also replace senses (sense switching) for impaired. Haptic technologies are often limited to point-wise actuation. Here, we show that actuation in two-dimensional matrices instead creates a richer input. We describe the construction of a full-body garment for haptic communication with a distributed actuating network. The garment is divided into attachable-detachable panels or add-ons that each can carry a two dimensional matrix of actuating haptic elements. Each panel adds to an enhanced sensoric capability of the human- garment system so that together a 720° system is formed. The spatial separation of the panels on different body locations supports semantic and theme-wise separation of conversations conveyed by haptics. It also achieves directional faithfulness, which is maintaining any directional information about a distal stimulus in the haptic input.
Zur Herstellung von Spritzgussformeinsätzen kommen in der Regel spanende Verfahren zum Einsatz. In den letzten Jahren hat sich allerdings auch die additive Herstellung dieser Werkzeuge als zweckmäßig erwiesen. In der Produktentwicklung spielt die Agilität heute eine immer wichtigere Rolle. Um mögliche Potentiale des Additive Tooling im Rahmen des Agile Prototyping und um Unterschiede zu den konventionellen Herstellverfahren aufzuzeigen, werden Angebote für die Fertigung mehrerer Formeinsätze durch eine CNC- und HSC-Fertigung, sowie durch additive Herstellung angefragt und hinsichtlich Beschaffungskosten und -zeiten miteinander verglichen. Zudem erfolgt eine Bewertung der technischen Unterschiede. Aus diesen beiden Betrachtungen kann schließlich ein Profil über die drei Herstellverfahren abgeleitet werden, welches bei der anwendungsfallspezifischen Verfahrensauswahl unterstützen soll.
Many different methods, such as screen printing, gravure, flexography, inkjet etc., have been employed to print electronic devices. Depending on the type and performance of the devices, processing is done at low or high temperature using precursor- or particle-based inks. As a result of the processing details, devices can be fabricated on flexible or non-flexible substrates, depending on their temperature stability. Furthermore, in order to reduce the operating voltage, printed devices rely on high-capacitance electrolytes rather than on dielectrics. The printing resolution and speed are two of the major challenging parameters for printed electronics. High-resolution printing produces small-size printed devices and high-integration densities with minimum materials consumption. However, most printing methods have resolutions between 20 and 50 μm. Printing resolutions close to 1 μm have also been achieved with optimized process conditions and better printing technology.
The final physical dimensions of the devices pose severe limitations on their performance. For example, the channel lengths being of this dimension affect the operating frequency of the thin-film transistors (TFTs), which is inversely proportional to the square of channel length. Consequently, short channels are favorable not only for high-frequency applications but also for high-density integration. The need to reduce this dimension to substantially smaller sizes than those possible with today’s printers can be fulfilled either by developing alternative printing or stamping techniques, or alternative transistor geometries. The development of a polymer pen lithography technique allows scaling up parallel printing of a large number of devices in one step, including the successive printing of different materials. The introduction of an alternative transistor geometry, namely the vertical Field Effect Transistor (vFET), is based on the idea to use the film thickness as the channel length, instead of the lateral dimensions of the printed structure, thus reducing the channel length by orders of magnitude. The improvements in printing technologies and the possibilities offered by nanotechnological approaches can result in unprecedented opportunities for the Internet of Things (IoT) and many other applications. The vision of printing functional materials, and not only colors as in conventional paper printing, is attractive to many researchers and industries because of the added opportunities when using flexible substrates such as polymers and textiles. Additionally, the reduction of costs opens new markets. The range of processing techniques covers laterally-structured and large-area printing technologies, thermal, laser and UV-annealing, as well as bonding techniques, etc. Materials, such as conducting, semiconducting, dielectric and sensing materials, rigid and flexible substrates, protective coating, organic, inorganic and polymeric substances, energy conversion and energy storage materials constitute an enormous challenge in their integration into complex devices.
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.
OVVL (the Open Weakness and Vulnerability Modeller) is a tool and methodology to support threat modeling in the early stages of the secure software development lifecycle. We provide an overview of OVVL (https://ovvl.org), its data model and browser-based UI. We equally provide a discussion of initial experiments on how identified threats in the design phase can be aligned with later activities in the software lifecycle (issue management and security testing).
Automotive service suppliers are keen to invent products that help to reduce particulate matter pollution substantial, but governance worldwide are not yet ready to introduce this retrofitting of helpful devices statutory. To develop a strategy how to introduce these devices to the market based on user needs is the objective of our research. The contribution of this paper is three-fold: we will provide an overview of the current options of particulate matter pollution solutions (I). This corpus is used to come to a more precise description of the specific needs and wishes of target groups (II). Finally, a representative empirical study via social media channels with German car owners will help to develop a strategy to introduce retrofit devices into the German market (III).
The recent successes and wide spread application of compute intensive machine learning and data analytics methods have been boosting the usage of the Python programming language on HPC systems. While Python provides many advantages for the users, it has not been designed with a focus on multiuser environments or parallel programming - making it quite challenging to maintain stable and secure Python workflows on a HPC system. In this paper, we analyze the key problems induced by the usage of Python on HPC clusters and sketch appropriate workarounds for efficiently maintaining multi-user Python software environments, securing and restricting resources of Python jobs and containing Python processes, while focusing on Deep Learning applications running on GPU clusters.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
This paper explains the realization of a concept for research-oriented photonics education. Using the example of the integration of an actual PhD project, it is shown how students are familiarized with the topic of research and scientific work in the first semesters. Typical research activities are included as essential parts of the learning process. Research should be made visible and tangible for the students. The authors will present all aspects of the learning environment, their impressions and experiences with the implemented scenario, as well as first evaluation results of the students.
Sustainable design of equipment for process intensification requires a comprehensive and correct identification of relevant stakeholder requirements, design problems and tasks crucial for innovation success. Combining the principles of the Quality Function Deployment with the Importance-Satisfaction Analysis and Contradiction Analysis of requirements gives an opportunity to define a proper process innovation strategy more reliably and to develop an optimal process intensification technology with less secondary engineering and ecological problems.
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.