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Time-Sensitive Networking (TSN) is the most promising time-deterministic wired communication approach for industrial applications. To extend TSN to "IEEE 802.11" wireless networks two challenging problems must be solved: synchronization and scheduling. This paper is focused on the first one. Even though a few solutions already meet the required synchronization accuracies, they are built on expensive hardware that is not suited for mass market products. While next Wi-Fi generation might support the required functionalities, this paper proposes a novel method that makes possible high-precision wireless synchronization using commercial low-cost components. With the proposed solution, a standard deviation of synchronization error of less than 500 ns can be achieved for many use cases and system loads on both CPU and network. This performance is comparable to modern wired real-time field busses, which makes the developed method a significant contribution for the extension of the TSN protocol to the wireless domain.
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 a self-supervised 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 supervision. 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 representations. Thus, the resulting latent representations can serve as robust appearance cues for tracking even over large temporal distances where no reliable spatio-temporal features can 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.
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks
(2021)
Decision explanations of machine learning black-box models are often generated by applying Explainable AI (XAI) techniques. However, many proposed XAI methods produce unverified outputs. Evaluation and verification are usually achieved with a visual interpretation by humans on individual images or text. In this preregistration, we propose an empirical study and benchmark framework to apply attribution methods for neural networks developed for images and text data on time series. We present a methodology to automatically evaluate and rank attribution techniques on time series using perturbation methods to identify reliable approaches.
A Hybrid Optoelectronic Sensor Platform with an Integrated Solution‐Processed Organic Photodiode
(2021)
Hybrid systems, unifying printed electronics with silicon‐based technology, can be seen as a driving force for future sensor development. Especially interesting are sensing elements based on printed devices in combination with silicon‐based high‐performance electronics for data acquisition and communication. In this work, a hybrid system integrating a solution‐processed organic photodiode in a silicon‐based system environment, which enables flexible device measurement and application‐driven development, is presented. For performance evaluation of the integrated organic photodiode, the measurements are compared to a silicon‐based counterpart. Therefore, the steady state response of the hybrid system is presented. Promising application scenarios are described, where a solution‐processed organic photodiode is fully integrated in a silicon system.
To demonstrate how deep learning can be applied to industrial applications with limited training data, deep learning methodologies are used in three different applications. In this paper, we perform unsupervised deep learning utilizing variational autoencoders and demonstrate that federated learning is a communication efficient concept for machine learning that protects data privacy. As an example, variational autoencoders are utilized to cluster and visualize data from a microelectromechanical systems foundry. Federated learning is used in a predictive maintenance scenario using the C-MAPSS dataset.
Herzfehler sind weltweit die häufigste Form von angeborenen Organdefekten. In unterschiedlichen Studien wird die Inzidenz zumeist zwischen vier und elf von 1.000 Lebendgeburten angegeben (1–5). Im Rahmen der multizentrischen PAN-Studie (PAN: Prävalenz angeborener Herzfehler bei Neugeborenen), welche die Häufigkeit angeborener Herzfehler bei Neugeborenen in Deutschland zwischen Juli 2006 und Juni 2007 untersuchte, ergab sich eine Gesamtprävalenz von 107,6 pro 10.000 Lebendgeburten. Gegenstand dieser Arbeit sind Untersuchungen an Implantaten zur Behandlung von Atriumseptumdefekten (ASD). Vorhofseptumdefekte machen mit 17,0%, nach den Ventrikelseptumdefekten (VSD) mit 48,9%die zweithäufigste Art von Herzfehlern aus (6, 7).Als Vorhofseptumdefekte werden Öffnungen in der Scheidewand zwischen den Herzvorhöfen bezeichnet. Bei der Therapie eines ASD ist der minimalinvasive Verschluss mittels sogenannter Okkluder heute das Mittel der Wahl. Diese werden über einen femoralen Zugang im Rahmen einer Herzkatheteruntersuchung unter Ultraschallkontrolle und Durchleuchtung an die Implantationsstelle vorgeschoben und dort platziert(8). Die Okkluder bestehen in der Regel aus einem Drahtgeflecht aus Nitinol und haben die typische Form eines sogenannten Doppelschirmchens. Dabei weichen die unterschiedlichen Okkluder der einzelnen Firmen hinsichtlich Form und Beschaffenheit oft erheblich voneinander ab. Derzeit gibt es keine Untersuchungsmethode, die die auf dem Markt befindlichen Okkluder hinsichtlich ihrer mechanischen Eigenschaften vergleichbar macht. Diese Arbeit solleinen Beitrag erbringen, um grundlegende, die Okkludermodelle charakterisierende Parameter zu schaffen, um so deren interindividuelle Vergleichbarkeit zu ermöglichen. Hierzu werden in-vitro Messungen durchgeführt, welche geeignet sind das Verhalten der untersuchten Modelle unter unterschiedlichen Bedingungen und bei variierenden Defektgrößen zu charakterisieren.
MINT-College TIEFE
(2021)
Das Projekt MINT-College TIEFE konnte in der zweiten Förderperiode die verschiedenen Maßnahmen der vorangegangenen Förderperiode weiter ausbauen und verstetigen. Die Angebote im Rahmen des Projekts MINT-College TIEFE begleiteten die Studierenden über den Student-Life-Cycle hinweg über das komplette Studium der technischen Studiengänge, beginnend in der Schule und endend beim Übergang in den Beruf. Um die Qualität der Lehre an der Hochschule Offenburg zu verbessern, wurden darüber hinaus verschiedene digital unterstützte Lehrformate weiterentwickelt und ausgebaut. Zentrale Angebote des MINT-College, das 2019 zentrale Einrichtung der Hochschule Offenburg wurde, sind die für die Studieneingangsphase entwickelten Angebote der Einführungstage, des Mentorenprogramms, der Brückenkurse, des Lernzentrums und Angebote für den Übergang in den Beruf, wie das Gründerbüro. Die mediendidaktischen Unterstützungsangebote für Lehrende unterstützten den Lernkulturwandel an der Hochschule. Es wurden systematisch nachhaltige Strukturen aufgebaut, um Innovationen für das Lehren und das Lernen auch künftig entwickeln, erproben und etablieren zu können.
Dementia is a clinical diagnosis reflecting many possible underlying pathologies, for example, vascular dementia and neurodegenerative disorders such as frontotemporal dementia, Lewy body-type disorder or Alzheimer’s disease (AD). The breakthrough of 99mtechnetium-labelled perfusion tracers in the 1990s resulted in many SPECT studies of flow changes in AD. In the first decade of 2000, the role of perfusion SPECT was shifted from diagnosis towards differential diagnosis, parallel to the growing attention for diagnosing early stages of dementia. Previously a diagnosis based largely on a process of exclusion, new guidelines have emerged increasingly employing positive criteria to establish the diagnosis, including neuroimaging biomarkers. Nowadays, FDG PET has largely limited the role of perfusion SPECT, although it is still considered a valuable and cost-effective alternative when PET is not available.
Investigation of the Angle Dependency of Self-Calibration in Multiple-Input-Multiple-Output Radars
(2021)
Multiple-Input-Multiple-Output (MIMO) is a key technology in improving the angular resolution (spatial resolution) of radars. In MIMO radars the amplitude and phase errors in antenna elements lead to increase in the sidelobe level and a misalignment of the mainlobe. As the result the performance of the antenna channels will be affected. Firstly, this paper presents analysis of effect of the amplitude and phase errors on angular spectrum using Monte-Carlo simulations. Then, the results are compared with performed measurements. Finally, the error correction with a self-calibration method is proposed and its angle dependency is evaluated. It is shown that the values of the errors change with an incident angle, which leads to a required angle-dependent calibration.
PET and SPECT in Psychiatry
(2021)
This book provides a comprehensive overview of the use of PET and SPECT in the classic psychiatric disorders such as depression, bipolar disorder, anxiety disorders, and schizophrenia. In addition, it discusses the application of these functional neuroimaging techniques in a variety of other conditions, including sleep disorders, eating disorders, autism, and chronic fatigue syndrome. The new edition has been extensively revised and updated to reflect the latest advances and results in nuclear imaging within the field. Most chapters are written jointly by a clinical psychiatrist and a nuclear medicine expert to ensure a multidisciplinary approach. This state of the art compendium will be of value for all who have an interest in the field of neuroscience, from psychiatrists and radiologists/nuclear medicine specialists to interested general practitioners and cognitive psychologists. Companion volumes on the use of PET and SPECT in neurology and for the imaging of neurobiological systems complete a trilogy.
eLetter zum Artikel "Plague Through History" von Nils Chr. Stenseth, veröffentlicht in Science, Vol. 321, Issue 5890, Seite 773-774 (doi.org/10.1126/science.1161496)
Estimation of Scattering and Transfer Parameters in Stratified Dispersive Tissues of the Human Torso
(2021)
The aim of this study is to understand the effect of the various layers of biological tissues on electromagnetic radiation in a certain frequency range. Understanding these effects could prove crucial in the development of dynamic imaging systems under operating environments during catheter ablation in the heart. As the catheter passes through some arterial paths in the region of interest inside the heart through the aorta, a three-dimensional localization of the catheter is required. In this paper, a study is given on the detection of the catheter by using electromagnetic waves. Therefor, an appropriate model for the layers of the human torso is defined and simulated without and with an inserted electrode.
PET and SPECT in Neurology
(2021)
This book provides a comprehensive overview of the use of PET and SPECT in not only classic neurodegenerative disorders but also cerebrovascular disorders, brain tumors, epilepsy, head trauma, coma, sleeping disorders, and inflammatory and infectious diseases of the CNS. The new edition has been revised and updated to reflect recent advances and includes additional chapters, for example on the use of artificial intelligence and machine learning in imaging data analysis, the study of brain connectivity using PET and SPECT images, and the role of PET imaging in modulation of brain functioning by deep brain stimulation. The authors are renowned experts whose dedication to the investigation of neurological disorders through nuclear medicine technology has achieved international recognition. Most chapters are written jointly by a clinical neurologist and a nuclear medicine specialist to ensure a multidisciplinary approach. This state of the art compendium will be invaluable for neurologists and radiologists/nuclear medicine specialists and will also be informative for interested general practitioners and geriatricians. Companion volumes on PET and SPECT in psychiatry and in neurobiological systems complete a trilogy.
Artificial intelligence (AI), and in particular machine learning algorithms, are of increasing importance in many application areas but interpretability and understandability as well as responsibility, accountability, and fairness of the algorithms' results, all crucial for increasing the humans' trust into the systems, are still largely missing. Big industrial players, including Google, Microsoft, and Apple, have become aware of this gap and recently published their own guidelines for the use of AI in order to promote fairness, trust, interpretability, and other goals. Interactive visualization is one of the technologies that may help to increase trust in AI systems. During the seminar, we discussed the requirements for trustworthy AI systems as well as the technological possibilities provided by interactive visualizations to increase human trust in AI.
Fünf Jahre vor seinem Tod, im Jahr 1932, wurde der berühmte französische Komponist Maurice Ravel (1875–1937), der an einer frontotemporalen Demenz (M. Pick) mit primär progressiver Aphasie litt, bei einem Unfall verletzt, als er in einem Pariser Taxi saß. In diesem Fallbericht wird der Unfallmechanismus unter bestimmten Annahmen dargestellt und diskutiert. Ausgehend von diesen Überlegungen ist ein Unfall bei geringer Kollisionsgeschwindigkeit wahrscheinlich. Trotz eines Unfalls mit nur geringer Geschwindigkeit ist nicht von der Hand zu weisen, dass dieser Unfall zumindest zu einer deutlichen Verschlimmerung der Krankheitssymptome geführt haben könnte, da Ravel seit diesem Taxiunfall bis zu seinem Tod keine weiteren Kompositionen mehr vollendet hat.
In dieser Arbeit wird ein historischer Fallbericht des bis heute weit über seine Landesgrenzen bekannten italienischen Kriminalanthropologen Cesare Lombroso (1835–1909) vorgestellt. In diesem Fallbericht wird der berüchtigte und psychisch auffällige Dieb Pietro Bersone mit Hilfe eines sog. Hydrosphygmographen überführt, einem zur damaligen Zeit neuartigen technischen Gerät, das den Puls nicht-invasiv aufzeichnen konnte. Lombroso ist vermutlich einer der ersten, wenn nicht sogar der erste, der durch den Einsatz eines solchen Geräts die Idee zum „Lügendetektor“ vorweggenommen hat. Die vorgestellte Textstelle aus Lombrosos Buch „Neue Fortschritte in den Verbrecherstudien“ ist daher ein besonderes Fundstück auch für die Geschichte der Polygraphie.
eLetter zum Artikel "The Hannes hand prosthesis replicates the key biological properties of the human hand" von Matteo Laffranchi et al., veröffentlicht in Science Robotics, Vol. 5, Issue 46, eabb0467 (doi.org/10.1126/scirobotics.abb0467)
eLetter: "The ancient Capua leg from 300 BC and the 1941 air raid on the Royal College of Surgeons"
(2021)
eLetter zum Artikel "The College of Surgeons, London", veröffentlicht in Science, Vol. 93, Issue 2425, Seite 587 (DOI: 10.1126/science.93.2425.587).
Der verstärkte Einsatz von Wärmepumpen bei der Realisierung einer klimaneutralen Wärmeversorgung führt zu einer signifikanten Zunahme und Änderung der elektrischen Lasten in den Verteilnetzen. Daher gilt es, Wärmepumpen so zu steuern, dass sie Verteilnetze wenig belasten oder sogar unterstützen.
Inhalt des Projekts „PV²WP - PV Vorhersage für die netzdienliche Steuerung von Wärmepumpen“ (Projektlaufzeit 1.07.2018 – 30.06.2021) war die Demonstration eines neuen Ansatzes zur Steuerung von Heizungssystemen, die auf Wärmepumpen und thermischen Speichern basieren und in Kombination mit einer Photovoltaikanlage betrieben werden. Das übergeordnete Ziel war dabei die Verbesserung der Netzintegration und Smart-Grid-Tauglichkeit entsprechender Heizungssysteme durch eine kostengünstige Technologie bei gleichzeitiger Erhöhung der Wirtschaftlichkeit.
Dabei wurden drei zukunftsweisende Technologien in Kombination genutzt und demonstriert: wolkenkamerabasierte Kurzfristprognosen, prädiktive Steuerung und Regelung sowie machinelearning-basierte Systemmodellierung als Basis für die Optimierung. Als Demonstrationsumgebung diente mit dem Projekthaus Ulm ein real bewohntes Einfamilienhaus.Umweltforschung
IoT networks are increasingly used as entry points for cyberattacks, as often they offer low-security levels, as they may allow the control of physical systems and as they potentially also open the access to other IT networks and infrastructures. Existing intrusion detection systems (IDS) and intrusion prevention systems (IPS) mostly concentrate on legacy IT networks. Nowadays, they come with a high degree of complexity and adaptivity, including the use of artificial intelligence. It is only recently that these techniques are also applied to IoT networks. In this paper, we present a survey of machine learning and deep learning methods for intrusion detection, and we investigate how previous works used federated learning for IoT cybersecurity. For this, we present an overview of IoT protocols and potential security risks. We also report the techniques and the datasets used in the studied works, discuss the challenges of using ML, DL and FL for IoT cybersecurity and provide future insights.
The manufacturing of conventional electronics has become a highly complicated process, which requires intensive investment. In this context, printed electronics keeps attracting attention from both academia and industry. The primary reason is the simplification of the manufacturing process via additive printing technology such as ink-jet printing. Consequently, advantages are realized such as on-demand fabrication, minimal material waste and versatile choice of substrate materials. Central to the development of printed electronic circuits are printed transistors. Recently, metal oxide semiconductors such as indium oxide have become promising materials for the fabrication of printed transistors due to their high charge mobility. Furthermore, electrolyte-gating also provides benefits such as the low-voltage operation in sub-1 V regime due to the large gate capacitance provided by electrical double layers. This opens new possibilities to fabricate printed devices and circuits for niche applications.
To facilitate the design and fabrication of printed circuits, the development of compact models is necessary. However, most of the current works have focused on the study of the static behavior of transistors, while the in-depth understanding of other characteristics such as the dynamic or noise behavior is missing. To this end, the purpose of this work is the comprehensive study on capacitance and noise properties of inkjet-printed electrolyte-gated thin-film transistors (EGT) based on indium oxide semiconductors. Proper modeling approaches are also proposed to capture accurately the electrical behaviour, which can be further utilized to enable advanced analysis of digital, analog and mixed-signal circuits.
In this work, the capacitance of EGTs is characterized using voltage-dependent impedance spectroscopy. Intrinsic and extrinsic effects are carefully separated by using de-embedding test structures. Also, a dedicated equivalent circuit model is established to offer accurate simulations of the measured frequency response of the gate impedance. Based on that, it is revealed that top-gated EGTs have the potential to reach operation frequency in the kHz regime with proper optimizations of materials and printing process. Furthermore, a Meyer-like model is proposed to accurately capture the capacitance-voltage characteristics of the lumped terminal capacitance. Both parasitic and nonquasi-static effects are considered. This further enables the AC and transient analysis of complex circuits in circuit simulators.
Following, the study of noise properties in the field of printed electronics is conducted. Low-frequency noise of EGTs is characterized using a reliable experimental setup. By examining measured noise spectra of the drain current at various gate voltages, the number fluctuation with correlated mobility fluctuation has been determined as the primary noise mechanism. Based on that, normalized flat-band voltage noise can be determined as the key performance metrics, which is only 1.08 × 10−7 V^2 µm^2, significantly lower in comparison with other thin-film technologies, which are based on dielectric gating and semiconductors such as IZO and IGZO. A plausible reason could be the large gate capacitance offered by the electrical double layers. This renders EGT technology useful for low-noise and sensitive applications such as sensor periphery circuits.
Last but not least, various circuit designs based on EGT technology are proposed, including basic digital circuits such as inverters and ring oscillators. Their performance metrics such as the propagation delay and power consumption are extensively characterized. Also, the first design of a printed full-wave rectifier is presented by using diode-connected EGTs, which features near-zero threshold voltage. As a consequence, the presented rectifier can effectively process input voltage with a small amplitude of 100 mV and a cut-off frequency of 300 Hz, which is particularly attractive for the application domain of energy harvesting. Additionally, the previously established capacitance models are verified on those circuits, which provide a satisfactory agreement between the simulation and measurement data.
The Go programming language is an increasingly popular language but some of its features lack a formal investigation. This article explains Go's resolution mechanism for overloaded methods and its support for structural subtyping by means of translation from Featherweight Go to a simple target language. The translation employs a form of dictionary passing known from type classes in Haskell and preserves the dynamic behavior of Featherweight Go programs.
We describe a prototype for power line communi- cation for grid monitoring. The PLC receiver is used to gain information about the PLC channel and the current state of the power grid. The PLC receiver uses the communication signal to obtain an accurate estimate of the current channel and provides information which can be used as a basis for further processing with the aim to detect partial discharges and other anomalies in the grid. This monitoring of the power grid takes advantage of existing PLC infrastructure and uses the data signals, which are transmitted anyway to obtain a real-time measurement of the channel transfer function and the received noise signal. Since this signal is sampled at a high sampling rate compared to simpler measurement sensors, it contains valuable information about possible degradations in the grid which need to be addressed. While channel measurements are based on a received PLC signal, information about partial discharges or other sources of interference can be gathered by a PLC receiver in the absence of a transmit signal. A prototype based on Software Defined Radio has been developed, which implements the simultaneous communication and sensing for a power grid.
The term “attribute transfer” refers to the tasks of altering images in such a way, that the semantic interpretation of a given input image is shifted towards an intended direction, which is quantified by semantic attributes. Prominent example applications are photo realistic changes of facial features and expressions, like changing the hair color, adding a smile, enlarging the nose or altering the entire context of a scene, like transforming a summer landscape into a winter panorama. Recent advances in attribute transfer are mostly based on generative deep neural networks, using various techniques to manipulate images in the latent space of the generator. In this paper, we present a novel method for the common sub-task of local attribute transfers, where only parts of a face have to be altered in order to achieve semantic changes (e.g. removing a mustache). In contrast to previous methods, where such local changes have been implemented by generating new (global) images, we propose to formulate local attribute transfers as an inpainting problem. Removing and regenerating only parts of images, our “Attribute Transfer Inpainting Generative Adversarial Network” (ATI-GAN) is able to utilize local context information to focus on the attributes while keeping the background unmodified resulting in visually sound results.
The increasing use of artificial intelligence (AI) technologies across application domains has prompted our society to pay closer attention to AI’s trustworthiness, fairness, interpretability, and accountability. In order to foster trust in AI, it is important to consider the potential of interactive visualization, and how such visualizations help build trust in AI systems. This manifesto discusses the relevance of interactive visualizations and makes the following four claims: i) trust is not a technical problem, ii) trust is dynamic, iii) visualization cannot address all aspects of trust, and iv) visualization is crucial for human agency in AI.
The following describes a new method for estimating the parameters of an interior permanent magnet synchronous machine (IPMSM). For the estimation of the parameters the current slopes caused by the switching of the inverter are used to determine the unknowns of the system equations of the electrical machine. The angle and current dependence of the machine parameters are linearized within a PWM cycle. By considering the different switching states of the inverter, several system equations can be derived and a solution can be found within one PWM cycle. The use of test signals and filter-based approaches is avoided. The derived algorithm is explained and validated with measurements on a test bench.
The nonlinear behavior of inverters is mainly influenced by the interlocking and switching times of the semiconductors. In the following work, a method is presented that enables the possibility of an online identification of the switching times of the semiconductors. This information allows a compensation of the non-linear behavior, a reduction of the locking time and can be used for diagnostic purposes. First, a theoretical derivation of the method is made by considering different cases when switching of the inverter and deriving identification possibilities. The method is then extended so that the entire module is taken into account. Furthermore, a possible theoretical implementation is shown. After the methodology has been investigated with possible limitations, boundary conditions and with respect to real hardware, an implementation in the FPGA is performed. Finally, the results are presented, discussed
and further improvements are presented in an outlook.
Die vorliegende Arbeit gibt einen Überblick über das Verhältnis zwischen Nutzen und Einschränkungen eines frühneuzeitlichen Riefelharnisches auf die Biomechanik des Menschen. Zu den zentralen Ergebnissen gehört, dass die Rüstung eine gewisse Einschränkung der Beweglichkeit bringt, jedoch durch verschiedene mechanische Konzepte versucht wurde, diese größtmöglich zu minimieren. Besonders das sogenannte Geschübe stellt hierbei einen Kompromiss zwischen Beweglichkeit und Schutzfunktion dar und findet vor allem im Bereich der Gelenke Anwendung. Steife Strukturen werden an Stellen eingesetzt, die kaum Bewegungsfreiheit fordern. Zu diesen Bereichen gehören beispielsweise der Brustkorb oder obere Teile des Rückens. Der Vorteil der steiferen Teile der Rüstung ist ihre erhöhte Schutzfunktion, die ein geringeres Verletzungsrisiko mit sich bringt.
Im Jahre 2010 bot die Hochschule Offenburg ein Medizintechnikstudium mit dem Schwerpunkt ’Kardiologie, Elektrophysiologie und elektronische kardiologische Implantate’ als Bachelor- und später auch Masterstudiengang an. Ziel des auf diesen Schwerpunkt ausgelegten didaktischen Lehrkonzeptes ist die Vermittlung sofort anwendungsbereiten theoretischen Wissens und praktischen Könnens, welches die Absolventinnen und Absolventen in ihrer künftigen Berufsausübung in der Industrie oder als technische Partner der behandelnden Ärztinnen und Ärzte in hochspezialisierten klinischen Einrichtungen benötigen.
Aufgrund fehlender kommerzieller Angebote ist zur Umsetzung dieses Lehrkonzeptes die ingenieurtechnische Realisierung geeigneter Lehrmittel zwingend erforderlich. Dies betrifft die hard- und softwareseitige Erstellung visueller Demonstrationsmöglichkeiten für pathologische und implantatinduzierte Herzrhythmen, sowie die synthetische Bereitstellung originalgetreuer elektrokardiographischer Ableitsignale aus der klinischen Routine. Des Weiteren den Aufbau von in-vitro Trainingssystemen zu Therapien mit elektronischen kardiologischen Implantaten sowie zur Hochfrequenz-Katheterablation.
Insbesondere die Wahlfächer ’Programmierung von Herzschrittmachern’ und ‚Programmierung von Defibrillatoren’, deren Besuch den Teilnehmenden einen besonders raschen Berufseinstieg ermöglichen sollte, wurden in didaktischer Hinsicht in engem Bezug zum 4-Komponenten-Instruktionsdesign-Modell der Lehre gestaltet.
Durch den kontinuierlichen Einsatz der Instrumente der formativen Evaluation gelangen sowohl deutliche Verbesserungen am Gesamtkonzept der Lehrveranstaltungen als auch an den dort eingesetzten, selbst realisierten Lösungen des benannten speziellen Lehr- und Trainingsequipments.
Eine summative Evaluation des Lehrkonzeptes ist aufgrund seines Alleinstellungsmerkmals schwierig. Aus diesem Grund erschien die quantitative Prüfung des Einflusses eines Besuchs des praktisch orientierten Wahlfachs ’Programmierung von Herzschrittmachern’ auf die Note der kombinierten Abschlussklausur in den Fächern ’Elektrokardiographie’ und ’Elektrostimulation’ sinnvoll. In diese Evaluation eingeschlossen wurde eine Kohorte von 221 Studierenden, 76 Frauen und 145 Männer, von denen 93 am Wahlfach nicht teilnahmen und 128 die es besucht hatten.
Über 7 zusammengefasste Studienjahre zeigte sich, dass die praktische Ausbildung im Wahlfach ’Programmierung von Herzschrittmachern’ das Leistungsniveau der Studierenden der Medizintechnik in der kombinierten Abschlussprüfung ’Elektrokardiographie und Elektrostimulation’ deutlich beeinflusste.
Das im Rahmen dieser Arbeit mitgestaltete Lehrkonzept, die realisierten Lehrmaterialien und Lehrumgebungen wurden im Bachelor- und Masterstudiengang der Medizintechnik an der Hochschule Offenburg in den Praktika, Seminaren und Vorlesungen des Schwerpunktes ’Kardiologie, Elektrophysiologie und elektronische kardiologische Implantate’ vielfältig genutzt. Sie ermöglichten die Gestaltung interaktiver praktischer Weiterbildungsveranstaltungen für ärztliches und mittleres medizinisches Personal und für auf diesen Gebieten tätige medizintechnische Firmen.
Data Science
(2021)
Know-how für Data Scientists
• Übersichtliche und anwendungsbezogene Einführung
• Zahlreiche Anwendungsfälle und Praxisbeispiele aus unterschiedlichen Branchen
• Potenziale, aber auch mögliche Fallstricke werden aufgezeigt
Data Science steht derzeit wie kein anderer Begriff für die Auswertung großer Datenmengen mit analytischen Konzepten des Machine Learning oder der künstlichen Intelligenz. Nach der bewussten Wahrnehmung der Big Data und dabei insbesondere der Verfügbarmachung in Unternehmen sind Technologien und Methoden zur Auswertung dort gefordert, wo klassische Businss Intelligence an ihre Grenzen stößt.
Dieses Buch bietet eine umfassende Einführung in Data Science und deren praktische Relevanz für Unternehmen. Dabei wird auch die Integration von Data Science in ein bereits bestehendes Business-Intelligence-Ökosystem thematisiert. In verschiedenen Beiträgen werden sowohl Aufgabenfelder und Methoden als auch Rollen- und Organisationsmodelle erläutert, die im Zusammenspiel mit Konzepten und Architekturen auf Data Science wirken.
Diese 2., überarbeitete Auflage wurde um neue Themen wie Feature Selection und Deep Reinforcement Learning sowie eine neue Fallstudie erweitert.
Printed electronics (PE) offers flexible, extremely low-cost, and on-demand hardware due to its additive manufacturing process, enabling emerging ultra-low-cost applications, including machine learning applications. However, large feature sizes in PE limit the complexity of a machine learning classifier (e.g., a neural network (NN)) in PE. Stochastic computing Neural Networks (SC-NNs) can reduce area in silicon technologies, but still require complex designs due to unique implementation tradeoffs in PE. In this paper, we propose a printed mixed-signal system, which substitutes complex and power-hungry conventional stochastic computing (SC) components by printed analog designs. The printed mixed-signal SC consumes only 35% of power consumption and requires only 25% of area compared to a conventional 4-bit NN implementation. We also show that the proposed mixed-signal SC-NN provides good accuracy for popular neural network classification problems. We consider this work as an important step towards the realization of printed SC-NN hardware for near-sensor-processing.
Physically Unclonable Functions (PUFs) are hardware-based security primitives, which allow for inherent device fingerprinting. Therefore, intrinsic variation of imperfect manufactured systems is exploited to generate device-specific, unique identifiers. With printed electronics (PE) joining the internet of things (IoT), hardware-based security for novel PE-based systems is of increasing importance. Furthermore, PE offers the possibility for split-manufacturing, which mitigates the risk of PUF response readout by third parties, before commissioning. In this paper, we investigate a printed PUF core as intrinsic variation source for the generation of unique identifiers from a crossbar architecture. The printed crossbar PUF is verified by simulation of a 8×8-cells crossbar, which can be utilized to generate 32-bit wide identifiers. Further focus is on limiting factors regarding printed devices, such as increased parasitics, due to novel materials and required control logic specifications. The simulation results highlight, that the printed crossbar PUF is capable to generate close-to-ideal unique identifiers at the investigated feature size. As proof of concept a 2×2-cells printed crossbar PUF core is fabricated and electrically characterized.
Die Erfindung betrifft ein Verfahren zur Synchronisation eines Netzwerkgeräts für die drahtlose Kommunikation, insbesondere eines Netzwerk-Endgeräts, in einem Drahtlosnetzwerk, wobei das Netzwerkgerät einen integrierten Schaltkreis für die drahtlose Kommunikation (IWC), eine Synchronisationsevent-Detektoreinrichtung (SED) für das Detektieren von Synchronisationsevents, einen steuerbaren Clock-Generator (CCG) für das Erzeugen eines synchronisierten Zeitsignals TCCGund eine Synchronisationssteuereinrichtung (SCD) zur Steuerung des Synchronisationsvorgangs des Netzwerkgeräts umfasst. In dem Netzwerkgerät werden während einer Synchronisationsphase folgende Verfahrensschritte durchgeführt: Zunächst wird ein Synchronisations-Frame empfangen und ein Synchronisations-Timestamp TAPdetektiert. Anschließend wird ein Timestamp TBmittels einer im IWC enthaltenen IWC-Clock erzeugt, der die Empfangszeit des Synchronisations-Frames definiert. In einem weiteren Schritt wird an einem Port des IWC ein Potenzialwechsel erzeugt, der einen Synchronisationsevent darstellt. Weiterhin wird ein Timestamp TSEmittels der IWC-Clock erzeugt, der den Zeitpunkt des Synchronisationsevents definiert. Die SED detektiert den Synchronisationsevent durch Auswerten der zeitlichen Länge des Potenzialwechsels des Ports des IWC und erzeugt einen Timestamp TSunter Verwendung des synchronisierten Zeitsignals TCCG, wobei der Timestamp TSdenselben Zeitpunkt des Synchronisationsevents definiert wie der Timestamp TSE. Die Timestamps TAP, TB, TSEund TS, die mittels Verarbeitung von ein oder mehreren Synchronisationsevent-Frames gemäß den Schritten (a) bis (d) ermittelt wurden, werden dann zur Synchronisierung des vom CCG erzeugten synchronisierten Zeitsignals TCCGauf das Master-Zeitsignal verwendet.
Das hier vorgestellte System verbindet das neue Konzept der Peer-to-Peer-Navigation mit dem Einsatz von Augmented Reality zur Unterstützung von bettseitig durchgeführten externen Ventrikeldrainagen. Das sehr kompakte und genaue Gesamtsystem beinhaltet einen Patiententracker mit integrierter Kamera, eine Augmented-Reality-Brille mit Kamera und eine Punktionsnadel bzw. einen Pointer mit zwei Trackern, mit dessen Hilfe die Anatomie des Patienten aufgenommen wird. Die exakte Position und Richtung der Punktionsnadel wird unter Zuhilfenahme der aufgenommenen Landmarken berechnet und über die Augmented-Reality-Brille für den Chirurgen sichtbar auf dem Patienten dargestellt. Die Methode zur Kalibrierung der statischen Transformationen zwischen Patiententracker und daran befestigter Kamera beziehungsweise zwischen den Trackern der Punktionsnadel sind für die Genauigkeit sehr wichtig und werden hier vorgestellt. Das Gesamtsystem konnte in vitro erfolgreich getestet werden und bestätigt den Nutzen eines Peer-to-Peer-Navigationssystems.
Objective: To quantify the effect of inhaled 5% carbon-dioxide/95% oxygen on EEG recordings from patients in non-convulsive status epilepticus (NCSE).
Methods: Five children of mixed aetiology in NCSE were given high flow of inhaled carbogen (5% carbon dioxide/95% oxygen) using a face mask for maximum 120s. EEG was recorded concurrently in all patients. The effects of inhaled carbogen on patient EEG recordings were investigated using band-power, functional connectivity and graph theory measures. Carbogen effect was quantified by measuring effect size (Cohen's d) between "before", "during" and "after" carbogen delivery states.
Results: Carbogen's apparent effect on EEG band-power and network metrics across all patients for "before-during" and "before-after" inhalation comparisons was inconsistent across the five patients.
Conclusion: The changes in different measures suggest a potentially non-homogeneous effect of carbogen on the patients' EEG. Different aetiology and duration of the inhalation may underlie these non-homogeneous effects. Tuning the carbogen parameters (such as ratio between CO2 and O2, duration of inhalation) on a personalised basis may improve seizure suppression in future.
Significant progress in the development and commercialization of electrically conductive adhesives has been made. This makes shingling a very attractive approach for solar cell interconnection. In this study, we investigate the shading tolerance of two types of solar modules based on shingle interconnection: first, the already commercialized string approach, and second, the matrix technology where solar cells are intrinsically interconnected in parallel and in series. An experimentally validated LTspice model predicts major advantages for the power output of the matrix layout under partial shading. Diagonal as well as random shading of a 1.6-m2 solar module is examined. Power gains of up to 73.8 % for diagonal shading and up to 96.5 % for random shading are found for the matrix technology compared to the standard string approach. The key factor is an increased current extraction due to lateral current flows. Especially under minor shading, the matrix technology benefits from an increased fill factor as well. Under diagonal shading, we find the probability of parts of the matrix module being bypassed to be reduced by 40 % in comparison to the string module. In consequence, the overall risk of hotspot occurrence in matrix modules is decreased significantly.
A versatile liquid metal (LM) printing process enabling the fabrication of various fully printed devices such as intra- and interconnect wires, resistors, diodes, transistors, and basic circuit elements such as inverters which are process compatible with other digital printing and thin film structuring methods for integration is presented. For this, a glass capillary-based direct-write method for printing LMs such as eutectic gallium alloys, exploring the potential for fully printed LM-enabled devices is demonstrated. Examples for successful device fabrication include resistors, p–n diodes, and field effect transistors. The device functionality and easiness of one integrated fabrication flow shows that the potential of LM printing is far exceeding the use of interconnecting conventional electronic devices in printed electronics.
Digital transformation strengthens the interconnection of companies in order to develop optimized and better customized, cross-company business models. These models require secure, reliable, and traceable evidence and monitoring of contractually agreed information to gain trust between stakeholders. Blockchain technology using smart contracts allows the industry to establish trust and automate cross-company business processes without the risk of losing data control. A typical cross-company industry use case is equipment maintenance. Machine manufacturers and service providers offer maintenance for their machines and tools in order to achieve high availability at low costs. The aim of this chapter is to demonstrate how maintenance use cases are attempted by utilizing hyperledger fabric for building a chain of trust by hardened evidence logging of the maintenance process to achieve legal certainty. Contracts are digitized into smart contracts automating business that increase the security and mitigate the error-proneness of the business processes.
The twin concept is increasingly used for optimization tasks in the context of Industry 4.0 and digitization. The twin concept can also help small and medium-sized enterprises (SME) to exploit their energy flexibility potential and to achieve added value by appropriate energy marketing. At the same time, this use of flexibility helps to realize a climate-neutral energy supply with high shares of renewable energies. The digital twin reflects real production, power flows and market influences as a computer model, which makes it possible to simulate and optimize on-site interventions and interactions with the energy market without disturbing the real production processes. This paper describes the development of a generic model library that maps flexibility-relevant components and processes of SME, thus simplifying the creation of a digital twin. The paper also includes the development of an experimental twin consisting of SME hardware components and a PLC-based SCADA system. The experimental twin provides a laboratory environment in which the digital twin can be tested, further developed and demonstrated on a laboratory scale. Concrete implementations of such a digital twin and experimental twin are described as examples.
In bimodal cochlear implant (CI) / hearing aid (HA) users a constant interaural time delay in the order of several milliseconds occurs due to differences in signal processing of the devices. For MED-EL CI systems in combination with different HA types, we have quantified the respective device delay mismatch (Zirn et al. 2015). In the current study, we investigate the effect of the device delay mismatch in simulated and actual bimodal listeners on sound localization accuracy.
To deal with the device delay mismatch in actual bimodal listeners we delayed the CI stimulation according to the measured HA processing delay and two other values. With all delay values highly significant improvements of the rms error in the localization task were observed compared to the test without the delay. The results help to narrow down the optimal patient-specific delay value.
Zeitliche Anpassung führt zu verbesserter Schalllokalisation bei bimodal versorgten CI-/HG-Trägern
(2021)
Bei bimodal versorgten Cochlea-Implantaten (CI) / Hörgerät (HG)-Trägern entsteht durch die unterschiedliche Signalverarbeitung der Geräte eine konstante interaurale Zeitverzögerung in der Größenordnung von mehreren Millisekunden. Für MED-EL CI-Systeme in Kombination mit verschiedenen HG-Typen haben wir den jeweiligen Device-Delay-Mismatch quantifiziert. In der aktuellen Studie untersuchen wir den Einfluss der Device-Delay-Mismatch bei simulierten und tatsächlichen bimodalen Hörern auf die Genauigkeit der Schalllokalisation.
Um den Device-Delay-Mismatch bei bimodal versorgten Patienten zu verringern, haben wir die CI-Stimulation um die gemessene HG-Signallaufzeit und zwei weitere Werte verzögert. Nach einer Angewöhnungsphase war der effektive Winkelfehler bei Verzögerung um die HG-Signallaufzeit hochsignifikant reduziert im Vergleich zu der Testkondition ohne CI-Verzögerung (mittlere Verbesserung: 11 % ; p < .01, Wilcoxon Signed Rank Test). Aber auch mit den beiden weiteren Verzögerungswerten wurden Verbesserungen erreicht. Anhand der Ergebnisse lässt sich der optimale patientenspezifische Verzögerungswert näher eingrenzen.
Recently, adversarial attacks on image classification networks by the AutoAttack (Croce and Hein, 2020b) framework have drawn a lot of attention. While AutoAttack has shown a very high attack success rate, most defense approaches are focusing on network hardening and robustness enhancements, like adversarial training. This way, the currently best-reported method can withstand about 66% of adversarial examples on CIFAR10. In this paper, we investigate the spatial and frequency domain properties of AutoAttack and propose an alternative defense. Instead of hardening a network, we detect adversarial attacks during inference, rejecting manipulated inputs. Based on a rather simple and fast analysis in the frequency domain, we introduce two different detection algorithms. First, a black box detector that only operates on the input images and achieves a detection accuracy of 100% on the AutoAttack CIFAR10 benchmark and 99.3% on ImageNet, for epsilon = 8/255 in both cases. Second, a whitebox detector using an analysis of CNN feature maps, leading to a detection rate of also 100% and 98.7% on the same benchmarks.