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Im Rahmen dieser Arbeit wurden Resorcinol-Formaldehyd-Aerogele zur Anwendung in Kreislaufwärmerohren (LHP) als Dochtmaterial entwickelt. Aerogele als Dochtmaterial bilden aufgrund der hohen Porosität und der effektiven Kapillarwirkung eine gute Grundvoraussetzung für Stoff- und Wärmetransport. Diese Eigenschaften können zu einer Verbesserung der Kühlleistung einer Wärmepumpe beitragen. Dazu wurden Aerogele in Dochtform synthetisiert und anschließend erfolgte die Bestimmung der skelettalen Dichte, umhüllenden Dichte, Porosität und Gaspermeabilität. Zusätzlich wurde ein Test zum Schwellverhalten entwickelt. Außerdem wurden die Proben zur Fa. Allatherm gesendet, um die Anforderungen an die entwickelten RFAerogele in Dochtform zu prüfen. Die mechanische Bearbeitbarkeit der Aerogele konnte verbessert werden. Die Porosität und die Gaspermeabilität der untersuchten Aerogele lagen in einem optimalen Bereich. Nur die Durchgangsporengröße der Aerogele, die mittels Gasblasendruck-Analyse bestimmt wurde, benötigt weitere Rezeptentwicklungen und Messungen, um die größte Durchgangspore in Richtung 1 µm einzugrenzen.
This volume of the series Springer Briefs in Space Life Sciences explains the physics and biology of radiation in space, defines various forms of cosmic radiation and their dosimetry, and presents a range of exposure scenarios. It also discusses the effects of radiation on human health and describes the molecular mechanisms of heavy charged particles’ deleterious effects in the body. Lastly, it discusses countermeasures and addresses the vital question: Are we ready for launch?
Written for researchers in the space life sciences and space biomedicine, and for master’s students in biology, physics, and medicine, the book will also benefit all non-experts endeavoring to understand and enter space.
Reinforcement learning (RL) algorithms should learn as much as possible about the environment but not the properties of the physics engines that generate the environment. There are multiple algorithms that solve the task in a physics engine based environment but there is no work done so far to understand if the RL algorithms can generalize across physics engines. In this work, we compare the generalization performance of various deep reinforcement learning algorithms on a variety of control tasks. Our results show that MuJoCo is the best engine to transfer the learning to other engines. On the other hand, none of the algorithms generalize when trained on PyBullet. We also found out that various algorithms have a promising generalizability if the effect of random seeds can be minimized on their performance.
The present thesis elucidates the development of (i) a series of small molecule inhibitors reacting in a covalent-irreversible manner with the targeted proteases and (ii) a fluorescently labeled activity-based probe as a pharmacological tool compound for investigation of specific functions of the mentioned enzymes in vitro. Herein, the rational design, organic synthesis and quantitative structure-activity-relationships are described extensively.
Facial emotion recognition is the task to classify human emotions in face images. It is a difficult task due to high aleatoric uncertainty and visual ambiguity. A large part of the literature aims to show progress by increasing accuracy on this task, but this ignores the inherent uncertainty and ambiguity in the task. In this paper we show that Bayesian Neural Networks, as approximated using MC-Dropout, MC-DropConnect, or an Ensemble, are able to model the aleatoric uncertainty in facial emotion recognition, and produce output probabilities that are closer to what a human expects. We also show that calibration metrics show strange behaviors for this task, due to the multiple classes that can be considered correct, which motivates future work. We believe our work will motivate other researchers to move away from Classical and into Bayesian Neural Networks.
In this paper we introduce the Perception for Autonomous Systems (PAZ) software library. PAZ is a hierarchical perception library that allow users to manipulate multiple levels of abstraction in accordance to their requirements or skill level. More specifically, PAZ is divided into three hierarchical levels which we refer to as pipelines, processors, and backends. These abstractions allows users to compose functions in a hierarchical modular scheme that can be applied for preprocessing, data-augmentation, prediction and postprocessing of inputs and outputs of machine learning (ML) models. PAZ uses these abstractions to build reusable training and prediction pipelines for multiple robot perception tasks such as: 2D keypoint estimation, 2D object detection, 3D keypoint discovery, 6D pose estimation, emotion classification, face recognition, instance segmentation, and attention mechanisms.
Validierung einer Web-Applikation zum Fern-Monitoring von Belastungs- und Erholungsparametern
(2020)
Simultan zur agilen Entwicklung einer Web-Applikation, die Parameter der Belastungs- und Beanspruchungssteuerung erfasst, wurden die implementierten Belastungs- und Erholungs-parameter an freiwilligen Testern/innen in der Praxis überprüft. Um sowohl die Applikation als auch die z.T. selbst entwickelten Kenngrößen auf ihre externe Validität hin zu bewerten, werden diese regressionsanalytisch bearbeitet.
Dieses Buch bietet einen leicht verständlichen Einstieg in die Thematik des Data Minings und der Prädiktiven Analyseverfahren. Als Methodensammlung gedacht, bietet es zu jedem Verfahren zunächst eine kurze Darstellung der Theorie und erklärt die zum Verständnis notwendigen Formeln. Es folgt jeweils eine Illustration der Verfahren mit Hilfe von Beispielen, die mit dem Programmpaket R erarbeitet werden.
Zum Abschluss wird eine einfache Möglichkeit präsentiert, mit der die Performancewerte verschiedener Verfahren mit statistischen Mitteln verglichen werden können. Zum Einsatz kommen hierbei geeignete Grafiken und Konfidenzintervalle.
Das Buch verzichtet nicht auf Theorie, es präsentiert jedoch so wenig Theorie wie möglich, aber so viel wie nötig und ist somit optimal für Studium und Selbststudium geeignet.
Fundamental hydrogen storage properties of TiFe-alloy with partial substitution of Fe by Ti and Mn
(2020)
TiFe intermetallic compound has been extensively studied, owing to its low cost, good volumetric hydrogen density, and easy tailoring of hydrogenation thermodynamics by elemental substitution. All these positive aspects make this material promising for large-scale applications of solid-state hydrogen storage. On the other hand, activation and kinetic issues should be amended and the role of elemental substitution should be further understood. This work investigates the thermodynamic changes induced by the variation of Ti content along the homogeneity range of the TiFe phase (Ti:Fe ratio from 1:1 to 1:0.9) and of the substitution of Mn for Fe between 0 and 5 at.%. In all considered alloys, the major phase is TiFe-type together with minor amounts of TiFe2 or \b{eta}-Ti-type and Ti4Fe2O-type at the Ti-poor and rich side of the TiFe phase domain, respectively. Thermodynamic data agree with the available literature but offer here a comprehensive picture of hydrogenation properties over an extended Ti and Mn compositional range. Moreover, it is demonstrated that Ti-rich alloys display enhanced storage capacities, as long as a limited amount of \b{eta}-Ti is formed. Both Mn and Ti substitutions increase the cell parameter by possibly substituting Fe, lowering the plateau pressures and decreasing the hysteresis of the isotherms. A full picture of the dependence of hydrogen storage properties as a function of the composition will be discussed, together with some observed correlations.
Die 2010er Jahre waren durch einen starken Anstieg der Mieten und der Kaufpreise gerade in den Ballungsräumen gekennzeichnet. Hieraus wird teilweise abgeleitet, dass Wohnen "die soziale Frage unserer Zeit" sei. In dieser Analyse wird auf der Grundlage des Sozio-oekonomischen Panels (SOEP) die Entwicklung der Wohnkostenbelastung im Längs- und Querschnitt analysiert. Außerdem wird die historische Bedeutung der sozialen Frage erläutert. Insgesamt zeigt sich, dass die starke Arbeitsmarktentwicklung in Kombination mit einer Reduktion der Wohnflächen die Wohnkostenbelastung bei vielen Haushalten konstant gehalten hat. Nur bei wenigen Haushalten gibt es tatsächlich einen merklichen Anstieg der Belastung, jedoch bei gleichzeitig gestiegener Zufriedenheit mit der Wohnsituation. Auch wenn Wohnen damit nicht als die soziale Frage unserer Zeit bezeichnet werden kann, brauchen doch zahlreiche Haushalte Unterstützung. Insbesondere aufgrund der virusbedingten Wirtschaftskrise im Jahr 2020 dürfte deren Zahl noch steigen. Die dafür zur Verfügung stehenden Instrumente wie das Wohngeld und Sozialwohnungen sollten gestärkt werden, aber gerade bei Sozialwohnungen sollte darauf geachtet werden, die soziale Treffsicherheit zu verbessern.
An essential measure of autonomy in assistive service robots is adaptivity to the various contexts of human-oriented tasks, which are subject to subtle variations in task parameters that determine optimal behaviour. In this work, we propose an apprenticeship learning approach to achieving context-aware action generalization on the task of robot-to-human object hand-over. The procedure combines learning from demonstration and reinforcement learning: a robot first imitates a demonstrator’s execution of the task and then learns contextualized variants of the demonstrated action through experience. We use dynamic movement primitives as compact motion representations, and a model-based C-REPS algorithm for learning policies that can specify hand-over position, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours. We additionally conduct a user study involving participants assuming different postures and receiving an object from a robot, which executes hand-overs by either imitating a demonstrated motion, or adapting its motion to hand-over positions suggested by the learned policy. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
Deep learning models are extensively used in various safety critical applications. Hence these models along with being accurate need to be highly reliable. One way of achieving this is by quantifying uncertainty. Bayesian methods for UQ have been extensively studied for Deep Learning models applied on images but have been less explored for 3D modalities such as point clouds often used for Robots and Autonomous Systems. In this work, we evaluate three uncertainty quantification methods namely Deep Ensembles, MC-Dropout and MC-DropConnect on the DarkNet21Seg 3D semantic segmentation model and comprehensively analyze the impact of various parameters such as number of models in ensembles or forward passes, and drop probability values, on task performance and uncertainty estimate quality. We find that Deep Ensembles outperforms other methods in both performance and uncertainty metrics. Deep ensembles outperform other methods by a margin of 2.4% in terms of mIOU, 1.3% in terms of accuracy, while providing reliable uncertainty for decision making.
Short summary
This dataset accompanies our paper
A. Mitrevski, P. G. Plöger, and G. Lakemeyer, "Representation and Experience-Based Learning of Explainable Models for Robot Action Execution," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
Contents
There are three zip archives included, each of them a dump of a MongoDB database corresponding to one of the three experiments in the paper:
Grasping a drawer handle (handle_drawer_logs.zip)
Grasping a fridge handle (handle_fridge_logs.zip)
Pulling an object (pull_logs.zip)
All three experiments were performed with a Toyota HSR. Only the data necessary for learning the models used in our experiments are included here.
Usage
After unzipping the archives, each database can be restored with the command
mongorestore [directory_name]
This will create a MongoDB database with the name of the directory (handle_drawer_logs, handle_fridge_logs, and pull_logs).
Code for processing the data and model learning can be found in our <a href="https://github.com/alex-mitrevski/explainable-robot-execution-models">GitHub repository.
Describing the elephant: a foundational model of human needs, motivation, behaviour, and wellbeing
(2020)
Models of basic psychological needs have been present and popular in the academic and lay literature for more than a century yet reviews of needs models show an astonishing lack of consensus. This raises the question of what basic human psychological needs are and if this can be consolidated into a model or framework that can align previous research and empirical study. The authors argue that the lack of consensus arises from researchers describing parts of the proverbial elephant correctly but failing to describe the full elephant. Through redefining what human needs are and matching this to an evolutionary framework we can see broad consensus across needs models and neatly slot constructs and psychological and behavioural theories into this framework. This enables a descriptive model of drives, motives, and well-being that can be simply outlined but refined enough to do justice to the complexities of human behaviour. This also raises some issues of how subjective well-being is and should be measured. Further avenues of research and how to continue building this model and framework are proposed.
Evaluation of a Multi-Layer 2.5D display in comparison to conventional 3D stereoscopic glasses
(2020)
In this paper we propose and evaluate a custom-build projection-based multilayer 2.5D display, consisting of three layers of images, and compare performance to a stereoscopic 3D display. Stereoscopic vision can increase the involvement and enhance game experience, however may induce possible side effects, e.g. motion sickness and simulator sickness. To overcome the disadvantage of multiple discrete depths, in our system perspective rendering and head-tracking is used. A study was performed to evaluate this display with 20 participants playing custom-designed games. The results indicated that the multi-layer display caused fewer side effects than the stereoscopic display and provided good usability. The participants also stated a better or equal spatial perception, while the cognitive load stayed the same.
Graph drawing with spring embedders employs a V x V computation phase over the graph's vertex set to compute repulsive forces. Here, the efficacy of forces diminishes with distance: a vertex can effectively only influence other vertices in a certain radius around its position. Therefore, the algorithm lends itself to an implementation using search data structures to reduce the runtime complexity. NVIDIA RT cores implement hierarchical tree traversal in hardware. We show how to map the problem of finding graph layouts with force-directed methods to a ray tracing problem that can subsequently be implemented with dedicated ray tracing hardware. With that, we observe speedups of 4x to 13x over a CUDA software implementation.
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.
Medien spielen eine Schlüsselrolle für die öffentliche Meinung und Akzeptanz neuer Technologien. Mit einer qualitativen Inhaltsanalyse journalistischer Artikel zum Elektrofahrrad wurden Akteure und ihre Einstellungen und Handlungen in Bezug auf das Elektrofahrrad untersucht. In die Analyse flossen 444 Artikel ausgewählter deutscher Qualitätsmedien aus dem Jahr 2018 ein. Die Untersuchung zeigt den gesellschaftlich relevanten Diskurs über Elektrofahrräder auf und bietet Anknüpfungspunkte für die Förderung von Individualmobilität und der Entwicklung zukunftsfähiger Mobilitätskonzepte.
OSC data
(2020)
This paper introduces FaceHaptics, a novel haptic display based on a robot arm attached to a head-mounted virtual reality display. It provides localized, multi-directional and movable haptic cues in the form of wind, warmth, moving and single-point touch events and water spray to dedicated parts of the face not covered by the head-mounted display.The easily extensible system, however, can principally mount any type of compact haptic actuator or object. User study 1 showed that users appreciate the directional resolution of cues, and can judge wind direction well, especially when they move their head and wind direction is adjusted dynamically to compensate for head rotations. Study 2 showed that adding FaceHaptics cues to a VR walkthrough can significantly improve user experience, presence, and emotional responses.
Diese etablierte Formelsammlung enthält und erklärt mathematische Formeln innerhalb ökonomischer Zusammenhänge, wie sie in den Wirtschaftswissenschaften und in der wirtschaftswissenschaftlichen Praxis unbedingt notwendig sind. Das Verständnis der Formeln und deren praktische Anwendung werden durch nützliche Hilfen und erklärliche Beispiele sinnvoll unterstützt, so dass der Kontext wirtschaftsmathematischer Formeln klar und verständlich dargestellt wird. Diese Formelsammlung ist ein unverzichtbares Tool für Studierende der Wirtschaftswissenschaften, aber auch ein nützliches Nachschlagewerk für Verantwortliche aus Wirtschaft, Politik und Lehre.