Refine
H-BRS Bibliography
- yes (11) (remove)
Departments, institutes and facilities
Document Type
- Part of a Book (11) (remove)
Year of publication
- 2017 (11) (remove)
Language
- English (11) (remove)
Keywords
- GC/MS (2)
- domestic robots (2)
- robot competitions (2)
- stem cells (2)
- Adaptive Case Management (1)
- Additives (1)
- Analytical pyrolysis (1)
- BPMS (1)
- Biomineralization (1)
- Bond graphs (1)
Solid-Phase Microextraction (SPME) is a very simple and efficient, solventless sample preparation method, invented by Pawliszyn and coworkers at the University of Waterloo (Canada) in 1989. This method has been widely used in different fields of analytical chemistry since its first applications to environmental and food analysis. SPME integrates sampling, extraction, concentration and sample introduction into a single solvent-free step. The method saves preparation time, disposal costs and can improve detection limits. It has been routinely used in combination with gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS) and successfully applied to a wide variety of ompounds, especially for the extraction of volatile and semi-volatile organic compounds from environmental, biological and food samples.
Since the last twenty years, SPME in headspace (HS) mode is used as a valuable sample preparation technique for identifying degradation products in polymers and for determination of rest monomers and other light-boiling substances in polymeric materials. For more than ten years, our laboratory has been involved in projects focused on the application of HS-SPME-GC/MS for the characterization of polymeric materials from many branches of manufacturing and building industries. This book chapter describes the application examples of this technique for identifying volatile organic compounds (VOCs), additives and degradation products in industrial plastics, rubber, and packaging materials.
Service robots performing complex tasks involving people in houses or public environments are becoming more and more common, and there is a huge interest from both the research and the industrial point of view. The RoCKIn@Home challenge has been designed to compare and evaluate different approaches and solutions to tasks related to the development of domestic and service robots. RoCKIn@Home competitions have been designed and executed according to the benchmarking methodology developed during the project and received very positive feedbacks from the participating teams. Tasks and functionality benchmarks are explained in detail.
Systemunterstützung für wissensintensive Geschäftsprozesse – Konzepte und Implementierungsansätze
(2017)
Telecollaborating and communicating in online contexts using English as a Lingua Franca (ELF) requires students to develop multiple literacies in addition to foreign language skills and intercultural communicative competence. This chapter looks at the intersection of technology and teaching ELF, examining mutual contributions of technologies, more specifically Web 2.0, and ELF to each other, and the challenges in designing and implementing collaboration projects across cultures. Moreover, it looks at how the development of digital competencies in ELF (DELF) can be enhanced through the implementation of Web 2.0 mediated intercultural dialogues. The detail of the research design including internet tools used, participants and tasks are also discussed. Data analysis points to a positive attitude towards telecollaboration, also providing confirmation of some of the problems identified in theoretical framework, such as different levels of personal engagement.
Integrating Bond Graph-Based Fault Diagnosis and Fault Accommodation Through Inverse Simulation
(2017)
RoCKIn@Work was focused on benchmarks in the domain of industrial robots. Both task and functionality benchmarks were derived from real world applications. All of them were part of a bigger user story painting the picture of a scaled down real world factory scenario. Elements used to build the testbed were chosen from common materials in modern manufacturing environments. Networked devices, machines controllable through a central software component, were also part of the testbed and introduced a dynamic component to the task benchmarks. Strict guidelines on data logging were imposed on participating teams to ensure gathered data could be automatically evaluated. This also had the positive effect that teams were made aware of the importance of data logging, not only during a competition but also during research as useful utility in their own laboratory. Tasks and functionality benchmarks are explained in detail, starting with their use case in industry, further detailing their execution and providing information on scoring and ranking mechanisms for the specific benchmark.