Refine
Year of publication
- 2018 (84) (remove)
Document Type
- Conference Proceeding (84) (remove)
Conference Type
- Konferenzartikel (62)
- Konferenz-Abstract (14)
- Konferenz-Poster (3)
- Sonstiges (3)
- Konferenzband (2)
Keywords
- RoboCup (3)
- 5G mobile communication (2)
- Access protocols (2)
- Decoding (2)
- Gamification (2)
- Mikroelektronik (2)
- Multiuser detection (2)
- Payloads (2)
- Physical layer (2)
- access protocols (2)
- decoding (2)
- network coding (2)
- 3D-Druck von leitfähigen Materialien (1)
- 3D-Time-of-Flight Cameras (1)
- Affective Computing (1)
- Ageing (1)
- Assistive Technologies (1)
- Atrial fibrillation (1)
- Atrioventricular delay (1)
- Augmented Reality (1)
- Batteries (1)
- Biventricular pacing (1)
- CRC (1)
- Cardiac resynchronization therapy (1)
- CoBot (1)
- Context-awareness (1)
- Deaf-Blindness (1)
- Electrochemistry (1)
- Emotion Recognition (1)
- Energiemanagement (1)
- Energy Harvesting (EH) (1)
- Eyetracking, Technisches Zeichnen (1)
- FPGA (1)
- Finite element analysis (1)
- Flexibilisierung des Lernortes (1)
- Fractionated atrial signals (1)
- Fractionated ventricular signals (1)
- Gedruckte Elektronik (PE) (1)
- Gender in Science and Technology Studies (STS), digitalization, interactive documentary, participation (1)
- Greifsystemen (1)
- Harmonic analysis (1)
- Herzrhythmusmodell (1)
- Hochfrequenzablation (1)
- Human-Robot Collaboration (1)
- Intellectual Properties (1)
- Knowledge-based Innovation (1)
- Left atrial ECG (1)
- Left atrial delay (1)
- Left cardiac ECG (1)
- Lithium niobate (1)
- Lithium-ion battery (1)
- Low-Power-SoC-Systeme (1)
- MEMS (1)
- MPC (1)
- Mensch-Roboter-Kollaboration (1)
- Metallization (1)
- Mikrostruktur (1)
- Modelling (1)
- PV Applications, Smart PV, PV Battery Systems, PV Power Supplies (1)
- Photovoltaic (1)
- Plastizität (1)
- Rehabilitation (1)
- Roboter (1)
- Robotics (1)
- Robots (1)
- Safe Speed and Separation Monitoring. (1)
- Schaltungsdesign (1)
- Screencast (1)
- Signal averaging ECG (1)
- Simulation (1)
- Smart Grid (1)
- Smart wearables (1)
- Social Robots (1)
- Soft- und Hardcore-Prozessoren (1)
- Soziale Roboter (1)
- Spectral-temporal mapping (1)
- Stahl (1)
- Statistikvideos (1)
- Substrates (1)
- System-on-Chip (1)
- TRIZ (1)
- Tablet Lückenskript (1)
- Task Analysis (1)
- Transesophageal electrocardiography (1)
- Ventricular tachycardia (1)
- Videoclip (1)
- Wearables (1)
- Wishbone (1)
- accelerometer (1)
- cloud security (1)
- cluster (1)
- cross-industry innovation (1)
- cyclic plasticity (1)
- eco-innovation (1)
- elektrische Felder (1)
- gedruckter Sensorik (1)
- glass (1)
- gyroscope (1)
- hot work tool steel (1)
- inertial measurement unit (1)
- innovation management (1)
- kardiale Resynchronisationstherapie (1)
- laser material processing (1)
- machine learning (1)
- particle coarsening (1)
- pigment paste (1)
- printing technologies (1)
- process engineering (1)
- project-based learning (1)
- scanning electron microscope (SEM) (1)
- surface treatment (1)
- temperature dependency (1)
- thermische Felder (1)
Institute
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (40)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (19)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (13)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (11)
- Fakultät Wirtschaft (W) (10)
- INES - Institut für nachhaltige Energiesysteme (7)
- ACI - Affective and Cognitive Institute (4)
- WLRI - Work-Life Robotics Institute (2)
- CRT - Campus Research & Transfer (1)
- Zentrale Einrichtungen (1)
Open Access
- Closed Access (43)
- Open Access (35)
- Bronze (7)
- Closed (6)
The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach.
A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm.
The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.
With the need for automatic control based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear behaviour of the components but also certain unknown process dynamics like their internal control logic. At the Institute of Energy Systems Technology in Offenburg we have built a real-life microscale trigeneration plant and present in this paper a rational modelling procedure that satisfies the necessary characteristics for models to be applied in model predictive control for grid-reactive optimal scheduling of this complex energy system. These models are validated against experimental data and the efficacy of the methodology is discussed. Their application in the future for the optimal scheduling problem is also briefly motivated.
In this paper we report on the commercial background as well as resulting high-level architecture and design of a cloud-based system for cryptographic software protection and licensing. This is based on the experiences and insights gained in the context of a real-world commercial R&D project at Wibu-Systems AG, a company that specialises in software encryption and licensing solutions.
Brand identification has the potential of shaping individuals' attitudes, performance and commitment within learning and work contexts. We explore these effects, by incorporating elements of branded identification within gamified environments. We report a study with 44 employees, in which task performance and emotional outcomes are assessed in a real-world assembly scenario - namely, while performing a soldering task. Our results indicate that brand identification has a direct impact on individuals' attitude towards the task at hand: while instigating positive emotions, aversion and reactance also arise.
Optische Navigationssysteme weisen bisher eine eindeutige Trennung zwischen nachverfolgendem Gerät (Tool Tracker) und nachverfolgten Geräten (Tracked Tools) auf. In dieser Arbeit wird ein neues Konzept vorgestellt, dass diese Trennung aufhebt: Jedes Tracked Tool ist gleichzeitig auch Tool Tracker und besteht aus Marker-LEDs sowie mindestens einer Kamera, mit deren Hilfe andere Tracker in Lage und Orientierung nachverfolgt werden können. Bei Verwendung von nur einer Kamera geschieht dies mittels Pose Estimation, ab zwei Kameras werden die Marker-LEDs trianguliert. Diese Arbeit beinhaltet die Vorstellung des neuen Peer-To-Peer-Tracking-Konzepts, einen sehr schnellen Pose-Estimation-Algorithmus für beliebig viele Marker sowie die Klärung der Frage, ob die mit Pose Estimation erreichbare Genauigkeit vergleichbar mit der eines Stereo-Kamera-Systems ist und den Anforderungen an die chirurgische Navigation gerecht wird.
In a Semi-autonomic cloud auditing architecture we weaved in privacy enhancing mechanisms [15] by applying the public key version of the Somewhat homomorphic encryption (SHE) scheme from [4]. It turns out that the performance of the SHE can be significantly improved by carefully deriving relevant crypto parameters from the concrete cloud auditing use cases for which the scheme serves as a privacy enhancing approach. We provide a generic algorithm for finding good SHE parameters with respect to a given use case scenario by analyzing and taking into consideration security, correctness and performance of the scheme. Also, to show the relevance of our proposed algorithms we apply it to two predominant cloud auditing use cases.
This paper describes the use of the single-linkage hierarchical clustering method in outlier detection for manufactured metal work pieces. The main goal of the study is to group defects that occur 5 mm into a work piece from the edge, i.e., the border of the metal work piece. The goal is to remove defects outside the area of interest as outliers. According to the assumptions made for the performance criteria, the single-linkage method has achieved better results compared to other agglomeration methods.
In public transportation, the motor pool often consists of various different vehicles bought over a duration of many years. Sometimes, they even differ within one batch bought at the same time. This poses a considerable challenge in the storage and allocation of spare parts, especially in the event of damage to a vehicle. Correctly assigning these parts before the vehicle reaches the workshop could significantly reduce both the downtime and, therefore, the actual costs for companies. In order to achieve this, the current software uses a simple probability calculation. To improve the performance, the data of specific companies was analysed, preprocessed and used with several modelling techniques to classify and, therefore, predict the spare parts to be used in the event of a faulty vehicle. We summarize our experience running through the steps of the Cross Industry Standard Process for Data Mining and compare the performance to the previously used probability. Gradient Boosting Trees turned out to be the best modeling technique for this special case.