Refine
Year of publication
- 2017 (125) (remove)
Document Type
- Conference Proceeding (74)
- Article (reviewed) (31)
- Part of a Book (5)
- Article (unreviewed) (5)
- Letter to Editor (4)
- Book (2)
- Bachelor Thesis (1)
- Master's Thesis (1)
- Periodical Part (1)
- Report (1)
Conference Type
- Konferenzartikel (48)
- Konferenz-Abstract (19)
- Konferenz-Poster (3)
- Sonstiges (3)
- Konferenzband (1)
Language
- English (125) (remove)
Keywords
- CST (5)
- HF-Ablation (5)
- Games (4)
- CRT (3)
- Computer Games (3)
- Computerspiele (3)
- Ermüdung (3)
- Game Design (3)
- Gamification (3)
- RoboCup (3)
Institute
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (50)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (43)
- Fakultät Wirtschaft (W) (18)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (15)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (13)
- ACI - Affective and Cognitive Institute (7)
- INES - Institut für nachhaltige Energiesysteme (6)
- IfTI - Institute for Trade and Innovation (4)
- WLRI - Work-Life Robotics Institute (3)
- Zentrale Einrichtungen (2)
Open Access
- Closed Access (56)
- Open Access (52)
- Closed (5)
- Bronze (4)
- Diamond (1)
- Gold (1)
We present a two-dimensional (2D) planar chromatographic separation of estrogenic active compounds on RP-18 W (Merck, 1.14296) phase. A mixture of 8 substances was separated using a solvent mix consisting of hexane, ethyl acetate, acetone (55:15:10, v/v) in the first direction and of acetone and water (15:10, v/v) in the second direction. Separation was performed on an RP-18 W plate over a distance of 70 mm. This 2D-separation method can be used to quantify 17α-ethinylestradiol (EE2) in an effect-directed analysis, using the yeast strain Saccharomyces cerevisiae BJ3505. The test strain (according to McDonnell) contains the estrogen receptor. Its activation by estrogen active compounds is measured by inducing the reporter gene lacZ which encodes the enzyme β-galactosidase. This enzyme activity is determined on plate by using the fluorescent substrate MUG (4-methylumbelliferyl-β-d-galactopyranoside).
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset where, a subspace is the subset of dimensions of the data. But exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, thus, parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage, firstly, the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation has shown linear speedup. Secondly, we are developing an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
Modelling and Simulation of Microscale Trigeneration Systems Based on Real- Life Experimental Data
(2017)
For the shift of the energy grid towards a smarter decentralised system flexible microscale trigeneration systems will play an important role due to their ability to support the demand side management in buildings. However to harness their potential modern control methods like model predictive control must be implemented for their optimal scheduling and control. To implement such supervisory control methods, first, simple analytical models representing the behaviour of the components need to be developed. At the Institute of Energy System Technologies in Offenburg we have built a real-life microscale trigeneration plant and present in this paper the models based on experimental data. These models are qualitatively validated and their application in the future for the optimal scheduling problem is briefly motivated.
Microscale trigeneration systems are highly flexible in their operation and thus offer the technical possibility for peak load shifting in building demand side management. However to harness their potential modern control methods such as model predictive control must be implemented for their optimal scheduling. In literature the need for experimental investigation of microscale trigeneration systems to identify typical characteristics of the components and their interactions has been identified. On a real-life setup control specific information of the components is collected and lessons learnt during commissioning of the equipment is shared. The data is analysed to draw the vital characteristics of the system and it will be used for creating models of the components that can be utilised for optimal control.
Biological in situ methanation: Gassing concept and feeding strategy for enhanced performance
(2017)
The expansion of fluctuating renewable electricity production from wind and solar energy requires huge storage capacities. Power-to-gas (PtG) can contribute to tackle that issue via a two-step process, the electrolytic production of hydrogen and a subsequent methanation step (with additional CO2). The resulting fully grid compatible methane, also known as synthetic natural gas (SNG), can be both stored and transported in the vast existing natural gas infrastructure.
To overcome current major drawbacks of PtG, the relatively low efficiency and the high costs, we developed an improved method for the methanation step. In our approach we use a further development of the biological in situ methanation of hydrogen in biogas plants. Because this strategy uses directly internal residual CO2 from the biogas process in the biogas plant, you neither need additional external CO2 nor special reactors. Thus, PtG is combined with the production of an upgraded highly methane rich raw biogas.
However, the low solubility of hydrogen in aqueous solutions and the exploitation of the maximum biological production rates are still an engineering challenge for high performance biological in situ methanation.
In our experiments a setup with membrane gassing turned out to be most promising to ensure a sufficient gas liquid mass transfer of the hydrogen. The monitoring of hydrogenotrophic and aceticlastic archaea showed some adaption of these microbial subgroups to the hydrogen feed.
In order to achieve high methane concentrations of more than 90 % in the raw biogas a CO2-controlled hydrogen feed flow rate is suggested. For methane concentrations lower than 90 % simple current controlled hydrogen supply can be applied.
This book has emerged from lectures and courses given in recent years by the authors at their universities and shows how theoretical concepts of Business Intelligence are applied in SAP BW on HANA.
The authors developed a set of case studies guiding the student through the complete process of building an end-to-end BI system, based on a simple but realistic business scenario. The cases are designed in such a way that the application of many concepts such as staging, core data warehouse, data mart, reporting, etc., in SAP BW on HANA is introduced and demonstrated step by step.
Target Audience:
The cases are primarily designed for SAP BW beginners, who want a first introduction and hands-on experience with the latest version of BW on HANA. We briefly touch the general concepts of Business Intelligence and Data Warehousing. These concepts are discussed in many excellent books out in the market, which we don’t want to replace. The reader should either already be familiar with these concepts or should be willing to use the references we provide. Also, this book can NOT replace a complete consultant training for BW, but it can serve as a starting point for a journey into the world of SAP BW on HANA.
Time-of-Flight Cameras Enabling Collaborative Robots for Improved Safety in Medical Applications
(2017)
Human-robot collaboration is being used more and more in industry applications and is finding its way into medical applications. Industrial robots that are used for human-robot collaboration, cannot detect obstacles from a distance. This paper introduced the idea of using wireless technology to connect a Time-of-Flight camera to off-the-shelf industrial robots. This way, the robot can detect obstacles up to a distance of five meters. Connecting Time-of-Flight cameras to robots increases the safety in human-robot collaboration by detecting obstacles before a collision. After looking at the state of the art, the authors elaborated the different requirements for such a system. The Time-of-Flight camera from Heptagon is able to work in a range of up to five meters and can connect to the control unit of the robot via a wireless connection.
In safety critical applications wireless technologies are not widely spread. This is mainly due to reliability and latency requirements. In this paper a new wireless architecture is presented which will allow for customizing the latency and reliability for every single participant within the network. The architecture allows for building up a network of inhomogeneous participants with different reliability and latency requirements. The used TDMA scheme with TDD as duplex method is acting gentle on resources. Therefore participants with different processing and energy resources are able to participate.