Refine
Year of publication
- 2016 (277) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (54)
- Fachbereich Chemie und Biotechnologie (44)
- Fachbereich Bauingenieurwesen (35)
- Fachbereich Elektrotechnik und Informationstechnik (35)
- IfB - Institut für Bioengineering (35)
- Fachbereich Wirtschaftswissenschaften (31)
- Fachbereich Luft- und Raumfahrttechnik (28)
- Fachbereich Maschinenbau und Mechatronik (25)
- Fachbereich Energietechnik (17)
- INB - Institut für Nano- und Biotechnologien (15)
Document Type
- Article (116)
- Conference Proceeding (81)
- Part of a Book (27)
- Book (23)
- Other (10)
- Conference: Meeting Abstract (8)
- Report (5)
- Doctoral Thesis (3)
- Part of a Periodical (2)
- Patent (1)
- Talk (1)
Keywords
- Technical Operations Research (2)
- Additive Manufacturing (1)
- Annulus Fibrosus (1)
- Assessment (1)
- Asymptotic efficiency (1)
- Bacillus atrophaeus (1)
- Balance (1)
- Balanced hypergraph (1)
- Brandfall (1)
- Building Systems (1)
Für die Verarbeitung von natürlicher Sprache ist ein wichtiger Zwischenschritt das Parsing, bei dem für Sätze der natürlichen Sprache Ableitungsbäume bestimmt werden. Dieses Verfahren ist vergleichbar zum Parsen formaler Sprachen, wie z. B. das Parsen eines Quelltextes. Die Parsing-Methoden der formalen Sprachen, z. B. Bottom-up-Parser, können nicht auf das Parsen der natürlichen Sprache übertragen werden, da keine Formalisierung der natürlichen Sprachen existiert [3, 12, 23, 30].
In den ersten Programmen, die natürliche Sprache verarbeiten [32, 41], wurde versucht die natürliche Sprache mit festen Regelmengen zu verarbeiten. Dieser Ansatz stieß jedoch schnell an seine Grenzen, da die Regelmenge nicht vollständig sowie nicht minimal ist und wegen der benötigten Menge an Regeln schwer zu verwalten ist. Die Korpuslinguistik [22] bot die Möglichkeit, die Regelmenge durch Supervised-Machine-Learning-Verfahren [2] abzulösen.
Teil der Korpuslinguistik ist es, große Textkorpora zu erstellen und diese mit sprachlichen Strukturen zu annotieren. Zu diesen Strukturen gehören sowohl die Wortarten als auch die Ableitungsbäume der Sätze. Vorteil dieser Methodik ist es, dass repräsentative Daten zur Verfügung stehen. Diese Daten werden genutzt, um mit Supervised-Machine-Learning-Verfahren die Gesetzmäßigkeiten der natürliche Sprachen zu erlernen.
Das Maximum-Entropie-Verfahren ist ein Supervised-Machine-Learning-Verfahren, das genutzt wird, um natürliche Sprache zu erlernen. Ratnaparkhi [25] nutzt Maximum-Entropie, um Ableitungsbäume für Sätze der natürlichen Sprache zu erlernen. Dieses Verfahren macht es möglich, die natürliche Sprache (abgebildet als Σ∗) trotz einer fehlenden formalen Grammatik zu parsen.
This summer, RoboCup competitions were held for the 20th time in Leipzig, Germany. It was the second time that RoboCup took place in Germany, 10 years after the 2006 RoboCup in Bremen. In this article, we give an overview on the latest developments of RoboCup and what happened in the different leagues over the last decade. With its 20th edition, RoboCup clearly is a success story and a role model for robotics competitions. From our personal view point, we acknowledge this by giving a retrospection about what makes RoboCup such a success.
Mit steigenden Dämmstandards und höheren Komfortanforderungen der Nutzer gerät die Problematik der sommerlichen Überhitzung zunehmend in den Fokus. Um die Überhitzung möglichst gering zu halten, sind Maßnahmen und Lösungen zu entwickeln, die den potenziellen Kühlbedarf eines Gebäudes vermeiden sowie reduzieren. Im Rahmen des europäischen Forschungsprojektes BATIMASS wurden Techniken untersucht, die die sommerliche Raumtemperatur ohne zusätzliche Kühlung (passiv) oder aber mit energieeffizienter wasserbasierter Flächenkühlung (aktiv) reduzieren und die besonders für Gebäude in Stahl(leicht)bauweise geeignet sind. Dafür wurde die Methodik der thermisch äquivalenten Decke weiterentwickelt, um das thermische Verhalten von Profilblechdecken in Gebäuden für beide Lösungsansätze analysieren zu können. Darüber hinaus wurde der Einsatz von Phasenwechselmaterial (PCM) zur Steigerung der Speicherfähigkeit von leichten Decken mit besonders geringer thermischer Masse in Simulationen sowie im Labor untersucht und bewertet.
This article discusses the contrast between the information transportation companies provide to travellers and that of their brand messaging. Companies’ brand messaging often portrays the service they provide as pleasant, stress free and perfect. Customers and users of the service, on the other hand, often describe their experience of the service as a negative one. This article suggests that the brand value would be greater if transportation companies paid more attention to the users’ experience when designing their information systems, particularly in worst case scenarios.
The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning methods delivering only two-dimensional data, often termed seed size. However, three-dimensional traits, such as the volume or mass of single seeds, are very rarely determined in routine measurements. Here, we introduce a device named phenoSeeder, which enables the handling and phenotyping of individual seeds of very different sizes. The system consists of a pick-and-place robot and a modular setup of sensors that can be versatilely extended. Basic biometric traits detected for individual seeds are two-dimensional data from projections, three-dimensional data from volumetric measures, and mass, from which seed density is also calculated. Each seed is tracked by an identifier and, after phenotyping, can be planted, sorted, or individually stored for further evaluation or processing (e.g. in routine seed-to-plant tracking pipelines). By investigating seeds of Arabidopsis (Arabidopsis thaliana), rapeseed (Brassica napus), and barley (Hordeum vulgare), we observed that, even for apparently round-shaped seeds of rapeseed, correlations between the projected area and the mass of seeds were much weaker than between volume and mass. This indicates that simple projections may not deliver good proxies for seed mass. Although throughput is limited, we expect that automated seed phenotyping on a single-seed basis can contribute valuable information for applications in a wide range of wild or crop species, including seed classification, seed sorting, and assessment of seed quality.
Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.
Label-free Electrostatic Detection of DNA Amplification by PCR Using Capacitive Field-effect Devices
(2016)
A capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensor modified with a positively charged weak polyelectrolyte of poly(allylamine hydrochloride) (PAH)/single-stranded probe DNA (ssDNA) bilayer has been used for a label-free electrostatic detection of pathogen-specific DNA amplification via polymerase chain reaction (PCR). The sensor is able to distinguish between positive and negative PCR solutions, to detect the existence of target DNA amplicons in PCR samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process.