Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (1357)
- INB - Institut für Nano- und Biotechnologien (503)
- Fachbereich Chemie und Biotechnologie (472)
- Fachbereich Elektrotechnik und Informationstechnik (414)
- IfB - Institut für Bioengineering (410)
- Fachbereich Energietechnik (361)
- Fachbereich Luft- und Raumfahrttechnik (253)
- Fachbereich Maschinenbau und Mechatronik (148)
- Fachbereich Wirtschaftswissenschaften (116)
- Fachbereich Bauingenieurwesen (69)
Language
- English (3276) (remove)
Document Type
- Article (3276) (remove)
Keywords
- Einspielen <Werkstoff> (7)
- avalanche (5)
- Earthquake (4)
- FEM (4)
- Finite-Elemente-Methode (4)
- LAPS (4)
- biosensors (4)
- field-effect sensor (4)
- frequency mixing magnetic detection (4)
- CellDrum (3)
We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.
The concept of an injective affine embedding of the quantum states into a set of classical states, i.e., into the set of the probability measures on some measurable space, as well as its relation to statistically complete observables is revisited, and its limitation in view of a classical reformulation of the statistical scheme of quantum mechanics is discussed. In particular, on the basis of a theorem concerning a non-denseness property of a set of coexistent effects, it is shown that an injective classical embedding of the quantum states cannot be supplemented by an at least approximate classical description of the quantum mechanical effects. As an alternative approach, the concept of quasi-probability representations of quantum mechanics is considered.
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.
Biotechnological downstream processing is usually an elaborate procedure, requiring a multitude of unit operations to isolate the target component. Besides the disadvantageous space-time yield, the risks of cross-contaminations and product loss grow fast with the complexity of the isolation procedure. A significant reduction of unit operations can be achieved by application of magnetic particles, especially if these are functionalized with affinity ligands. As magnetic susceptible materials are highly uncommon in biotechnological processes, target binding and selective separation of such particles from fermentation or reactions broths can be done in a single step. Since the magnetizable particles can be produced from iron salts and low priced polymers, a single-use implementation of these systems is highly conceivable. In this article, the principles of magnetizable particles, their synthesis and functionalization are explained. Furthermore, applications in the area of reaction engineering, microfluidics and downstream processing are discussed focusing on established single-use technologies and development potential.
Fundamentals and ignition of a microplasma at 2.45 GHZ / Holtrup, Stephan ; Heuermann, Holger
(2009)
Different analytical approaches exist to describe the structural substance or wear reserve of sewer systems. The aim is to convert engineering assessments of often complex defect patterns into computational algorithms and determine a substance class for a sewer section or manhole. This analytically determined information is essential for strategic rehabilitation planning processes up to network level, as it corresponds to the most appropriate rehabilitation type and can thus provide decision-making support. Current calculation methods differ clearly from each other in parts, so that substance classes determined by the different approaches are only partially comparable with each other. The objective of the German R&D cooperation project ‘SubKanS’ is to develop a methodology for classifying the specific defect patterns resulting from the interaction of all the individual defects, and their severities and locations. The methodology takes into account the structural substance of sewer sections and manholes, based on real data and theoretical considerations analogous to the condition classification of individual defects. The result is a catalogue of defect patterns and characteristics, as well as associated structural substance classifications of sewer systems (substance classes). The methodology for sewer system substance classification is developed so that the classification of individual defects can be transferred into a substance class of the sewer section or manhole, eventually taking into account further information (e.g. pipe material, nominal diameter, etc.). The result is a validated methodology for automated sewer system substance classification.