Conference Proceeding
Refine
Year of publication
- 2024 (9)
- 2023 (35)
- 2022 (46)
- 2021 (48)
- 2020 (46)
- 2019 (74)
- 2018 (64)
- 2017 (66)
- 2016 (66)
- 2015 (71)
- 2014 (51)
- 2013 (57)
- 2012 (59)
- 2011 (44)
- 2010 (48)
- 2009 (53)
- 2008 (37)
- 2007 (44)
- 2006 (60)
- 2005 (23)
- 2004 (22)
- 2003 (22)
- 2002 (25)
- 2001 (12)
- 2000 (12)
- 1999 (7)
- 1998 (8)
- 1997 (8)
- 1996 (4)
- 1995 (4)
- 1993 (6)
- 1992 (3)
- 1991 (2)
- 1990 (1)
- 1989 (3)
- 1988 (3)
- 1986 (1)
- 1985 (2)
- 1984 (3)
- 1983 (2)
- 1981 (2)
- 1980 (1)
- 1979 (1)
- 1978 (3)
- 1975 (2)
- 1973 (2)
Institute
- Fachbereich Elektrotechnik und Informationstechnik (234)
- Fachbereich Medizintechnik und Technomathematik (210)
- Fachbereich Luft- und Raumfahrttechnik (183)
- Fachbereich Energietechnik (177)
- IfB - Institut für Bioengineering (148)
- Solar-Institut Jülich (110)
- Fachbereich Maschinenbau und Mechatronik (107)
- Fachbereich Bauingenieurwesen (75)
- ECSM European Center for Sustainable Mobility (52)
- Fachbereich Wirtschaftswissenschaften (51)
Language
- English (1162) (remove)
Document Type
- Conference Proceeding (1162) (remove)
Keywords
- Biosensor (25)
- CAD (7)
- Finite-Elemente-Methode (7)
- civil engineering (7)
- Bauingenieurwesen (6)
- Blitzschutz (6)
- Enterprise Architecture (5)
- Clusterion (4)
- Energy storage (4)
- Gamification (4)
Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer.
Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench.
The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019.
The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
We report on the synthesis and CO gas-sensing properties of mesoporous tin(IV) oxides (SnO2). For the synthesis cetyltrimethylammonium bromide (CTABr) was used as a structure-directing agent; the resulting SnO2 powders were applied as films to commercially available sensor substrates by drop coating. Nitrogen physisorption shows specific surface areas up to 160 m2·g-1 and mean pore diameters of about 4 nm, as verified by TEM. The film conductance was measured in dependence on the CO concentration in humid synthetic air at a constant temperature of 300 °C. The sensors show a high sensitivity at low CO concentrations and turn out to be largely insensitive towards changes in the relative humidity. We compare the materials with commercially available SnO2-based sensors.