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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.
Morphological transition of a rod-shaped phase into a string of spherical particles is commonly observed in the microstructures of alloys during solidification (Ratke and Mueller, 2006). This transition phenomenon can be explained by the classic Plateau-Rayleigh theory which was derived for fluid jets based on the surface area minimization principle. The quintessential work of Plateau-Rayleigh considers tiny perturbations (amplitude much less than the radius) to the continuous phase and for large amplitude perturbations, the breakup condition for the rod-shaped phase is still a knotty issue. Here, we present a concise thermodynamic model based on the surface area minimization principle as well as a non-linear stability analysis to generalize Plateau-Rayleigh’s criterion for finite amplitude perturbations. Our results demonstrate a breakup transition from a continuous phase via dispersed particles towards a uniform-radius cylinder, which has not been found previously, but is observed in our phase-field simulations. This new observation is attributed to a geometric constraint, which was overlooked in former studies. We anticipate that our results can provide further insights on microstructures with spherical particles and cylinder-shaped phases.
Neurostimulation durch Musik
(2020)
Was ist die Musik und wie wirkt sie sich auf den menschlichen Körper aus? Historisch betrachtet wird die Musik als etwas Göttliches aufgefasst, da sie eine äußerst große Wirkung auf die Emotionen des Menschen besitzt. Dieser Effekt wirkt sich auch psychosomatisch aus und kann das Denken und Handeln des Zuhörers beeinflussen und steuern. So lässt sich beispielsweise das Kaufverhalten allein durch die musikalische Begleitung deutlich manipulieren. Selbst die Motivation lässt sich mit passender Vertonung entweder steigern oder reduzieren. In der heutigen Zivilisation begleitet die Musik den Menschen alltäglich und wird zu vielen verschiedenen Zwecken verwendet. Somit ist die musikalische Stimulation als eine Art Psychotherapie zu werten, die häufig gezielt angewendet wird, aber im Beeinflussten unterbewusst stattfindet. Da natürlich immer noch offene Fragen bezüglich der genauen Wirkung von Musik auf das Gehirn bestehen, werden derzeit im Bereich der Neurowissenschaften viele Studien durchgeführt, um dieses Phänomen nachvollziehen zu können.
In der vorliegenden Arbeit werden fotografische Aufnahmen zweier verschiedener Abgüsse von Paganinis rechter Hand vorgestellt und näher beschrieben. Es handelt sich um einen mutmaßlich originalen Bronzeabguss, der vermutlich kurz nach Paganinis Tod auf dessen Totenbett abgenommen wurde, und eine in heutiger Zeit angefertigte Kopie aus Fiberplastik mit goldfarbenem Anstrich. Die Hand ist im proximalen Handgelenk stark abgewinkelt, was dafür spricht, dass die Hand des Toten auf einem Kissen gelegen haben könnte, um den Abguss vorzunehmen. Überdies zeigt sich eine verkrampfte Stellung der Finger und Hand, am ehesten infolge Totenstarre. Man findet zudem arthrotische Veränderungen sowie hervortretende Sehnen und atrophierte Muskulatur. Beim Bronzeabguss sind die beschriebenen Auffälligkeiten deutlicher zu erkennen. Ein 3D-Scan des Bronzeabgusses der rechten Hand Paganinis mit einem Strukturlichtscanner würde die Möglichkeit eröffnen, Messdaten der Hand zu erhalten.
Oesophageal Electrode Probe and Device for Cardiological Treatment and/or Diagnosis (US20200261024)
(2020)
An oesophageal electrode probe for bioimpedance measurement and/or for neurostimulation is provided; a device for transoesophageal cardiological treatment and/or cardiological diagnosis is also provided; a method for the open-loop or closed-loop control of a cardiological catheter ablation device and/or a cardiological, circulatory and/or respiratory support device is also provided. The oesophageal electrode probe comprises a bioimpedance measuring device for measuring the bioimpedance of at least one part of tissue surrounding the oesophageal electrode probe. The bioimpedance device comprises at least one first and one second electrode. The at least one first electrode is arranged on a side of the oesophageal electrode probe facing towards the heart. The at least one second electrode is arranged on a side of the oesophageal electrode probe facing away from the heart. The device comprises the oesophageal electrode probe and a control and/or evaluation device.
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.
We introduce an open source python framework named PHS-Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside the target function. Possible applications appear in expensive to evaluate numerical computations which strongly depend on hyperparameters such as machine learning. Bayesian optimization is chosen as a sample efficient method to propose the next query set of parameters.
Die industrielle Kommunikation war früher von relativ eingeschränkten, geschlossenen Feldbussystemen geprägt. Mit der zunehmenden Öffnung von Automatisierungsnetzen durch die horizontale und vertikale Integration in Produktionsanlagen entstehen gefährliche Angriffsflächen, die zum Diebstahl von Produktionsgeheimnissen, der Manipulation oder dem kompletten Lahmlegen der Produktionsprozesse führen können. Hieraus ergeben sich grundlegend neue Anforderung an die Datensicherheit, denen mit innovativen Lösungsansätzen begegnet werden muss.
Ziel des Forschungsvorhabens „SecureField“ war es, die Umsetzbarkeit und Anwendbarkeit des Ansatzes „(D)TLS-over-Anything“ zu untersuchen und nachzuweisen, sowie einen Werkzeugkasten zur Definition und Implementierung entsprechender Sicherheitslösungen vorzubereiten. Als langjährig etablierter Standard im IT-Umfeld stellte sich das (Datagram) Transport Layer Security ((D)TLS) Protokoll in Kombination mit einer industrie- bzw. automatisierungskompatiblen Public-Key-Infrastruktur (PKI) als äußerst vielversprechende Möglichkeit dar, Datensicherheit auch im OT-Umfeld zu erzielen. Hierbei sollten insbesondere KMU adressiert werden, für welche eigene Entwicklungsarbeiten in diesem Umfeld häufig zu aufwändig und technisch sowie wirtschaftlich zu riskant sind.
Mit „SecureField“ konnten Ergebnisse auf mehreren Ebenen erzielt werden. Zunächst konnte im Projektverlauf ein umfassendes und generisches Konzept zur Ende-zu-Ende-Absicherung von Kommunikationspfaden und -protokollen im industriellen Umfeld erarbeitet werden. Dieses Konzept besteht aus einem generischen Kommunikationsmodell sowie aus einem generischen Authentifikationsmodell.
Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
Electrolyte-gated thin-film transistors (EGTs) with indium oxide channel, and expected lifetime of three months, enable low-voltage operation (~1 V) in the field of printed electronics (PEs). The channel width of our printed EGTs is varied between 200 and 1000 μm, whereas a channel length between 10 and 100 μm is used. Due to the lack of uniform performance p-type metal oxide semiconductors, n-type EGTs and passive elements are used to design circuits. For logic gates, transistor-resistor logic has been employed so far, but depletion and enhancement-mode EGTs in a transistor-transistor logic boost the circuit performance in terms of delay and signal swing. In this article, the threshold voltage of the EGT, which determines the operation mode, is tuned through sizing of the EGTs channel geometry. The feasibility of both transistor operation modes is demonstrated for logic gates and ring oscillators. An inverter operating at a supply voltage of 1 V shows a maximum gain of 9.6 and a propagation delay time of 0.7 ms, which represents an improvement of ~ 2x for the gain and oscillation frequency, in comparison with the resistor-transistor logic design. Moreover, the power consumption is reduced by 6x.
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.
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.
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.
RETIS – Real-Time Sensitive Wireless Communication Solution for Industrial Control Applications
(2020)
Ultra-Reliable Low Latency Communications (URLLC) has been always a vital component of many industrial applications. The paper proposes a new wireless URLLC solution called RETIS, which is suitable for factory automation and fast process control applications, where low latency, low jitter, and high data exchange rates are mandatory. In the paper, we describe the communication protocol as well as the hardware structure of the network nodes for implementing the required functionality. Many techniques enabling fast, reliable wireless transmissions are used – short Transmission Time Interval (TTI), Time-Division Multiple Access (TDMA), MIMO, optional duplicated data transfer, Forward Error Correction (FEC), ACK mechanism. Preliminary tests show that reliable end-to-end latency down to 350 μs and packet exchange rate up to 4 kHz can be reached (using quadruple MIMO and standard IEEE 802.15.4 PHY at 250 kbit/s).
Die Erfindung betrifft eine Schaltungsanordnung (10) für ein Kraftfahrzeug, mit einer Hochvolt-Batterie (12) zum Speichern von elektrischer Energie, mit wenigstens einer elektrischen Maschine (14) zum Antreiben des Kraftfahrzeugs, mit einem Stromrichter (16), mittels welchem von der Hochvolt-Batterie (12) bereitstellbare Hochvolt-Gleichspannung in Hochvolt-Wechselspannung zum Betreiben der elektrischen Maschine (14) umwandelbar ist, und mit einem Ladeanschluss (20) zum Bereitstellen von elektrischer Energie zum Laden der Hochvolt-Batterie (12), wobei der Stromrichter (16) als ein Drei-Stufen-Stromrichter ausgebildet ist und wenigstens eine einer Phase (u) der elektrischen Maschine (14) zugeordnete Schaltereinheit (46) aufweist, welche zwei in Reihe geschaltete Schaltergruppen (52, 54) umfasst, die jeweils zwei in Reihe geschaltete IGBTs (T11, T12, T13, T14) aufweisen, wobei zwischen den IGBTs (T11, T12) einer der Schaltergruppen (52, 54) ein Anschluss (64) angeordnet ist, welcher direkt mit einer Leitung (34) des Ladeanschlusses (20) elektrisch verbunden ist.
The number of use cases for autonomous vehicles is increasing day by day especially in commercial applications. One important application of autonomous vehicles can be found within the parcel delivery section. Here, autonomous cars can massively help to reduce delivery efforts and time by supporting the courier actively. One important component of course is the autonomous vehicle itself. Nevertheless, beside the autonomous vehicle, a flexible and secure communication architecture also is a crucial key component impacting the overall performance of such system since it is required to allow continuous interactions between the vehicle and the other components of the system. The communication system must provide a reliable and secure architecture that is still flexible enough to remain practical and to address several use cases. In this paper, a robust communication architecture for such autonomous fleet-based systems is proposed. The architecture provides a reliable communication between different system entities while keeping those communications secure. The architecture uses different technologies such as Bluetooth Low Energy (BLE), cellular networks and Low Power Wide Area Network (LPWAN) to achieve its goals.
Die transösophageale Neurostimulation ist eine neue Therapieform und könnte unter anderem zur Schmerzlinderung während einer transösophagealen Linksherzstimulation angewendet werden. Sie ist in die Kategorie der Rückenmarksstimulation (SCS) einzuordnen, die die meist verwendete Technik der Neurostimulation ist. Die derzeit auf dem Markt vorhandenen Ösophaguskatheter werden bei einer elektrophysiologischen Untersuchung mit Ablation und transösophagealer Echokardiographie zur Temperaturüberwachung eingesetzt. Das Ziel dieser Arbeit war, das vorhandene Offenburger Herzrhythmusmodell, um die Wirbelsäule zu erweitern, einen neuen Ösophagus-Elektroden- Katheter für die transösophageale elektrische Stimulation des Rückenmarks zu modellieren und mittels 3D-Computer-Simulationen auf Ihre Wirksamkeit zu untersuchen.
Due to the rapidly increasing storage consumption worldwide, as well as the expectation of continuous availability of information, the complexity of administration in today’s data centers is growing permanently. Integrated techniques for monitoring hard disks can increase the reliability of storage systems. However, these techniques often lack intelligent data analysis to perform predictive maintenance. To solve this problem, machine learning algorithms can be used to detect potential failures in advance and prevent them. In this paper, an unsupervised model for predicting hard disk failures based on Isolation Forest is proposed. Consequently, a method is presented that can deal with the highly imbalanced datasets, as the experiment on the Backblaze benchmark dataset demonstrates.
Diffracted waves carry high resolution information that can help interpreting fine structural details at a scale smaller than the seismic wavelength. Because of the low signal-to-noise ratio of diffracted waves, it is challenging to preserve them during processing and to identify them in the final data. It is, therefore, a traditional approach to pick manually the diffractions. However, such task is tedious and often prohibitive, thus, current attention is given to domain adaptation. Those methods aim to transfer knowledge from a labeled domain to train the model, and then infer on the real unlabeled data. In this regard, it is common practice to create a synthetic labeled training dataset, followed by testing on unlabeled real data. Unfortunately, such procedure may fail due to the existing gap between the synthetic and the real distribution since quite often synthetic data oversimplifies the problem, and consequently the transfer learning becomes a hard and non-trivial procedure. Furthermore, deep neural networks are characterized by their high sensitivity towards cross-domain distribution shift. In this work, we present deep learning model that builds a bridge between both distributions creating a semi-synthetic datatset that fills in the gap between synthetic and real domains. More specifically, our proposal is a feed-forward, fully convolutional neural network for imageto-image translation that allows to insert synthetic diffractions while preserving the original reflection signal. A series of experiments validate that our approach produces convincing seismic data containing the desired synthetic diffractions.
A novel approach for synchronization and calibration of a camera and an inertial measurement unit (IMU) in the research-oriented visual-inertial mapping-and localization-framework maplab is presented. Mapping and localization are based on detecting different features in the environment. In addition to the possibility of creating single-case maps, the included algorithms allow merging maps to increase mapping accuracy and obtain large-scale maps. Furthermore, the algorithms can be used to optimize the collected data. The preliminary results show that after appropriate calibration and synchronization maplab can be used efficiently for mapping, especially in rooms and small building environments.
Machine learning (ML) has become highly relevant in applications across all industries, and specialists in the field are sought urgently. As it is a highly interdisciplinary field, requiring knowledge in computer science, statistics and the relevant application domain, experts are hard to find. Large corporations can sweep the job market by offering high salaries, which makes the situation for small and medium enterprises (SME) even worse, as they usually lack the capacities both for attracting specialists and for qualifying their own personnel. In order to meet the enormous demand in ML specialists, universities now teach ML in specifically designed degree programs as well as within established programs in science and engineering. While the teaching almost always uses practical examples, these are somewhat artificial or outdated, as real data from real companies is usually not available. The approach reported in this contribution aims to tackle the above challenges in an integrated course, combining three independent aspects: first, teaching key ML concepts to graduate students from a variety of existing degree programs; second, qualifying working professionals from SME for ML; and third, applying ML to real-world problems faced by those SME. The course was carried out in two trial periods within a government-funded project at a university of applied sciences in south-west Germany. The region is dominated by SME many of which are world leaders in their industries. Participants were students from different graduate programs as well as working professionals from several SME based in the region. The first phase of the course (one semester) consists of the fundamental concepts of ML, such as exploratory data analysis, regression, classification, clustering, and deep learning. In this phase, student participants and working professionals were taught in separate tracks. Students attended regular classes and lab sessions (but were also given access to e-learning materials), whereas the professionals learned exclusively in a flipped classroom scenario: they were given access to e-learning units (video lectures and accompanying quizzes) for preparation, while face-to-face sessions were dominated by lab experiments applying the concepts. Prior to the start of the second phase, participating companies were invited to submit real-world problems that they wanted to solve with the help of ML. The second phase consisted of practical ML projects, each tackling one of the problems and worked on by a mixed team of both students and professionals for the period of one semester. The teams were self-organized in the ways they preferred to work (e.g. remote vs. face-to-face collaboration), but also coached by one of the teaching staff. In several plenary meetings, the teams reported on their status as well as challenges and solutions. In both periods, the course was monitored and extensive surveys were carried out. We report on the findings as well as the lessons learned. For instance, while the program was very well-received, professional participants wished for more detailed coverage of theoretical concepts. A challenge faced by several teams during the second phase was a dropout of student members due to upcoming exams in other subjects.
One of the main requirements of spatially distributed Internet of Things (IoT) solutions is to have networks with wider coverage to connect many low-power devices. Low-Power Wide-Area Networks (LPWAN) and Cellular IoT(cIOT) networks are promising candidates in this space. LPWAN approaches are based on enhanced physical layer (PHY) implementations to achieve long range such as LoRaWAN, SigFox, MIOTY. Narrowband versions of cellular network offer reduced bandwidth and, simplified node and network management mechanisms, such as Narrow Band IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). Since the underlying use cases come with various requirements it is essential to perform a comparative analysis of competing technologies. This article provides systematic performance measurement and comparison of LPWAN and NB-IoT technologies in a unified testbed, also discusses the necessity of future fifth generation (5G) LPWAN solutions.
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowledge or supervision to associate data correctly into tracks. In this work, we present an unsupervised multiple object tracking approach based on visual features and minimum cost lifted multicuts. Our method is based on straight-forward spatio-temporal cues that can be extracted from neighboring frames in an image sequences without superivison. Clustering based on these cues enables us to learn the required appearance invariances for the tracking task at hand and train an autoencoder to generate suitable latent representation. Thus, the resulting latent representations can serve as robust appearance cues for tracking even over large temporal distances where no reliable spatio-temporal features could be extracted. We show that, despite being trained without using the provided annotations, our model provides competitive results on the challenging MOT Benchmark for pedestrian tracking.
Die Erfindung betrifft ein Verfahren zur Steuerung eines Geräts, insbesondere einer Handprothese oder eines Roboterarms, wobei wenigstens ein an oder im Bezug zu dem Gerät positionierter Marker von einer an einer Bedienperson angeordneten Kamera erkannt wird, wobei ab dem Erkennen des wenigstens einen Markers eine vordefinierte Bewegung der Bedienperson zusammen mit der Kamera erkannt wird und zum Auslösen einer entsprechenden Aktion des Geräts verwendet wird, wobei die vordefinierte Bewegung einer Bedienperson in Form eines Sehstrahls mittels Kamera-Tracking erkannt wird. Weiterhin betrifft die Erfindung eine Anordnung aus einem Gerät, insbesondere einer Handprothese oder eines Roboterarms, und einer AR-Brille zur Durchführung eines derartigen Verfahrens.
Mit der Implementierung sowie einer anschließenden aussagekräftigen Evaluierung, soll das, visuelle-inertiale Kartierungs- und Lokalisierungssystem maplab analysiert werden. Hierbei basiert die Kartierung bzw. Lokalisierung auf der Detektion von Umgebungsmerkmalen. Neben der Möglichkeit der Kartenerstellung besteht ferner die Option, mehrere Karten zu fusionieren und somit weitreichende Gebiete zu kartieren sowie für weitere Datenauswertungen zu nutzen. Aufgrund der Durchführung und Bewertung der Ergebnisse in unterschiedlichen Anwendungsszenarien zeigt sich, dass maplab besonders zur Kartierung von Räumen bzw. kleinen Gebäudekomplexen geeignet ist. Die Möglichkeit der Kartenfusionierung bietet weiterhin die Option, den Informationsgehalt von Karten zu erhöhen, welches die Effektivität für eine anschließende Lokalisierung steigert. Bei wachsender Kartierungsgröße hingegen zeigt sich jedoch eine Vergrößerung geometrischer Inkonsistenzen.
Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or video sequences. In this paper, we show that common up-sampling methods, i.e. known as up-convolution or transposed convolution, are causing the inability of such models to reproduce spectral distributions of natural training data correctly. This effect is independent of the underlying architecture and we show that it can be used to easily detect generated data like deepfakes with up to 100% accuracy on public benchmarks. To overcome this drawback of current generative models, we propose to add a novel spectral regularization term to the training optimization objective. We show that this approach not only allows to train spectral consistent GANs that are avoiding high frequency errors. Also, we show that a correct approximation of the frequency spectrum has positive effects on the training stability and output quality of generative networks.
Das vorliegende Buch behandelt lineare zeitdiskrete Regelverfahren und gliedert sich in zwei Teile mit ganz unterschiedlichen thematischen Schwerpunkten. In den ersten sechs Kapiteln steht die Analyse und Synthese von zeitdiskreten Regelungen im Bildbereich im Vordergrund. Im zweiten Teil des Buchs werden im Zeitbereich angesiedelte zeitdiskrete Reglerentwurfsverfahren behandelt. Dort dominieren Zustandsraumverfahren die Erläuterungen.
Diese Arbeit beschäftigt sich mit der Biomechanik der Halswirbelsäule (HWS) beim Umgang mit dem Smartphone. Die Kräfte, die auf Wirbelkörper, Wirbelgelenke, Bandscheiben, Muskeln und Bänder wirken, werden mit steigendem Flexionswinkel der HWS größer. Die Beschwerden hingegen, welche der Smartphone-Nacken hervorruft, sind meist akut und mit regelmäßiger Bewegung und der Stärkung der Nackenmuskulatur gut zu behandeln. Eine Therapie ist somit auch zur Vorbeugung geeignet. Doch die Langzeitauswirkungen sind nicht außer Acht zu lassen, denn durch die steigenden Nutzungsmöglichkeiten der Smartphones steigt auch der durchschnittliche tägliche Gebrauch stärker an. So wird vor allem die tägliche Bildschirmzeit bei Jugendlichen immer länger. Das aktuell noch akute Krankheitsbild des Smartphone-Nackens, das nur selten einen chronischen Verlauf nimmt und Langzeitschäden verursacht, könnte sich durch fehlende oder zu späte Maßnahmen zu einem größeren chronischen Krankheitsbild entwickeln.
本发明涉及一种用于生物阻抗测量和/或用于神经刺激的食道电极探针(10);用于经食道心脏病治疗和/或心脏病诊断的设备(100);以及一种用于控制或调节用于心脏导管消融装置和/或心脏、循环和/或肺支持装置的方法。食道电极探针包括生物阻抗测量装置,用于测量围绕食道电极探针的组织中的至少一部分组织的生物阻抗。生物阻抗装置包括至少一个第一电极和至少一个第二电极,其中至少一个第一电极(12A)布置在食道电极探针的面向心脏的一侧(14)上,并且至少一个第二电极(12B)布置在食道电极探针背离心脏的一侧(16)上。装置(100)包括食道电极探针(10)和控制和/或评估装置(30),其被配置用于从至少一个第一电极(12A)接收第一生物阻抗测量信号并从至少一个第二电极(12B)接收第二生物阻抗测量信号,并对这些信号进行比较,并且在比较的基础上产生控制信号。该控制信号可以是用于控制或调节心脏导管消融装置和/或心脏、循环和/或肺支持装置的信号。