Refine
Year of publication
Document Type
- Conference Proceeding (934)
- Article (reviewed) (558)
- Article (unreviewed) (124)
- Part of a Book (65)
- Master's Thesis (63)
- Contribution to a Periodical (58)
- Book (30)
- Bachelor Thesis (29)
- Patent (29)
- Letter to Editor (28)
Conference Type
- Konferenzartikel (734)
- Konferenz-Abstract (134)
- Sonstiges (34)
- Konferenz-Poster (22)
- Konferenzband (12)
Language
- English (1976) (remove)
Keywords
- RoboCup (32)
- Dünnschichtchromatographie (27)
- COVID-19 (23)
- Export (22)
- Machine Learning (19)
- Gamification (17)
- Kommunikation (15)
- Finite-Elemente-Methode (13)
- Government Measures (13)
- TRIZ (13)
Institute
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (589)
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (501)
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) (373)
- Fakultät Wirtschaft (W) (279)
- INES - Institut für nachhaltige Energiesysteme (167)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (157)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (146)
- Fakultät Medien (M) (ab 22.04.2021) (80)
- IMLA - Institute for Machine Learning and Analytics (71)
- ACI - Affective and Cognitive Institute (58)
Open Access
- Open Access (830)
- Closed Access (666)
- Closed (290)
- Bronze (136)
- Gold (75)
- Diamond (67)
- Hybrid (44)
- Grün (12)
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.
The Project "Schluckspecht" of the University of Offenburg consists of participating in the European marathon called "Shell Eco-Marathon"(SEM) which consists of designing and building from the beginning a vehicle with the greatest possible energy efficiency. The University of Offenburg has participated in this project since 1998.
The team that forms the Schluckspecht project is made up of around 30 students from the faculties of mechanical engineering, process engineering, electrical engineering, medical technology and computer science, as well as the degree in Audiovisual Communication. The team was founded in 1998 and since then students have been developing and building high efficiency vehicles to participate in the European marathon Shell Eco.
In this project, students can put into practice all the theoretical knowledge obtained during their studies. Also can be learned how to work interdisciplinarity as a team, a skill that for now, many companies or require or seek.
The following topics are discussed in the Schluckspecht project, which are also ideal for the work of students:
-Conception construction and production of high efficiency vehicles.
-Computational design and manufacture of lightweight components and sets.
-Development of lightweight components and sets from renewable raw materials.
-Construction and development of special test benches, for example: motor test bench.
-Implementation and optimization of control strategies for autonomous driving
-Mechanical and electrical integration of sensors for autonomous driving
-Ergonomic studies and optimization of the driver's cabin.
The objective of the project is to develop and manufacture research vehicles that make individual mobility as efficient as possible from an energy point of view. To achieve this, current and future issues of the industry are discussed. In this project, both the theoretical and practical part of the light construction of vehicles and the reduction of friction, the variety of propulsion concepts (electric thrusters, fuel cells, diesel/petrol engines, Stirling engines) and autonomous driving are investigated. The services of the University of Offenburg together with some external partners are grouped together to make this wonderful project work.
The Projekt-Sweaty is a project of the University of Applied Sciences of Offenburg, an autonomous robot is being developed that competes against a set of several international colleges and universities in the RoboCup.
"Sweaty" is a soccer-playing humanoid robot who participated in the RoboCup World Cup in Brazil for the first time in 2014.
RoboCup is a competition aimed at developing a robot soccer team that surpasses the human world champion team. The competition started in 1997 the first official RoboCup games and conferences were held with great success. More than 40 teams took part and more than 5,000 spectators attended. RoboCup’s rules change to promote advances in robot science and technology and to bring the league’s challenges closer to the real world.
Building a robot that plays football will not in itself generate a significant social and economic impact, but the realization will certainly be considered an important success for the field of robotics.
Thanks to the interaction of all the faculties, the team consists of professors and students from the fields of mechanical and process engineering, electrical engineering, information technology, and information and media technology. Students can use the project during their studies and use the knowledge acquired in practice to implement and through their own creative ideas complement.
Grey-box modelling combines physical and data-driven models to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling, as differential equations given by physical laws and neural networks can be combined in a single modelling framework. This simplifies the simulation and optimization and allows to consider irregularly-sampled data during training and evaluation of the model. We demonstrate this approach using two levels of model complexity; first, a simple parallel resistor-capacitor circuit; and second, an equivalent circuit model of a lithium-ion battery cell, where the change of the voltage drop over the resistor-capacitor circuit including its dependence on current and State-of-Charge is implemented as NODE. After training, both models show good agreement with analytical solutions respectively with experimental data.
Disturbances of the cardiac conduction system causing reentry mechanisms above the atrioventricular (AV) node are induced by at least one accessory pathway with different conducting properties and refractory periods. This work aims to further develop the already existing and continuously expanding Offenburg heart rhythm model to visualise the most common supraventricular reentry tachycardias to provide a better understanding of the cause of the respective reentry mechanism.
Patients with focal ventricular tachycardia are at risk of hemodynamic failure and if no treatment is provided the mortality rate can exceed 30%. Therefore, medical professionals must be adequately trained in the management of these conditions. To achieve the best treatment, the origin of the abnormality should be known, as well as the course of the disease. This study provides an opportunity to visualize various focal ventricular tachycardias using the Offenburg cardiac rhythm model.
Active participation of industrial enterprises in electricity markets - a generic modeling approach
(2021)
Industrial enterprises represent a significant portion of electricity consumers with the potential of providing demand-side energy flexibility from their production processes and on-site energy assets. Methods are needed for the active and profitable participation of such enterprises in the electricity markets especially with variable prices, where the energy flexibility available in their manufacturing, utility and energy systems can be assessed and quantified. This paper presents a generic model library equipped with optimal control for energy flexibility purposes. The components in the model library represent the different technical units of an industrial enterprise on material, media, and energy flow levels with their process constraints. The paper also presents a case study simulation of a steel-powder manufacturing plant using the model library. Its energy flexibility was assessed when the plant procured its electrical energy at fixed and variable electricity prices. In the simulated case study, flexibility use at dynamic prices resulted in a 6% cost reduction compared to a fixed-price scenario, with battery storage and the manufacturing system making the largest contributions to flexibility.
Effective medium theories (EMT) are powerful tools to calculate sample averaged thermoelectric material properties of composite materials. However, averaging over the heterogeneous spatial distribution of the phases can lead to incorrect estimates of the thermoelectric transport properties and the figure of merit ZT in compositions close to the percolation threshold. This is particularly true when the phases’ electronic properties are rather distinct leading to pronounced percolation effects. The authors propose an alternative model to calculate the thermoelectric properties of multi‐phased materials that are based on an expanded nodal analysis of random resistor networks (RRN). This method conserves the information about the morphology of the individual phases, allowing the study of the current paths through the phases and the influence of heterogeneous charge transport and cluster formation on the effective material properties of the composite. The authors show that in composites with strongly differing phases close to the percolation threshold the thermoelectric properties and the ZT value are always dominated exclusively by one phase or the other and never by an average of both. For these compositions, the individual samples display properties vastly different from EMT predictions and can be exploited for an increased thermoelectric performance.
The increasing number of prosumers and the accompanying greater use of decentralised energy resources (DERs) bring new opportunities and challenges for the traditional electricity systems and the electricity markets. Microgrids, virtual power plants (VPPs), peer-to-peer (P2P) trading and federated power plants (FPPs) propose different schemes for prosumer coordination and have the potential of becoming the new paradigm of electricity market and power system operation. This paper proposes a P2P trading scheme for energy communities that negotiates power flows between participating prosumers with insufficient renewable power supply and prosumers with surplus supply in such a way that the community welfare is maximized while avoiding critical grid conditions. For this purpose, the proposed scheme is based on an Optimal Power Flow (OPF) problem with a Multi-Bilateral Economic Dispatch (MBED) formulation as an objective function. The solution is realized in a fully decentralized manner on the basis of the Relaxed Consensus + Innovations (RCI) algorithm. Network security is ensured by a tariff-based system organized by a network agent that makes use of product differentiation capabilities of the RCI algorithm. It is found that the proposed mechanism accurately finds and prevents hazardous network operations, such as over-voltage in grid buses, while successfully providing economic value to prosumers’ renewable generation within the scope of a P2P, free market.
Pure orbital blowout fractures occur within the confines of the internal orbital wall. Restoration of orbital form and volume is paramount to prevent functional and esthetic impairment. The anatomical peculiarity of the orbit has encouraged surgeons to develop implants with customized features to restore its architecture. This has resulted in worldwide clinical demand for patient-specific implants (PSIs) designed to fit precisely in the patient’s unique anatomy. Material extrusion or Fused filament fabrication (FFF) three-dimensional (3D) printing technology has enabled the fabrication of implant-grade polymers such as Polyetheretherketone (PEEK), paving the way for a more sophisticated generation of biomaterials. This study evaluates the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the relevant design, biomechanical, and morphological parameters. The performance of the implants is studied as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predict the high durability of the implants, and the maximum deformation values were under one-tenth of a millimeter (mm) domain in all the implant profile configurations. The circular patterned implant (0.9 mm) had the best performance score. The study demonstrates that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor.