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Our university carries out various research projects. Among others, the project Schluckspecht is an interdisciplinary work on different ultra-efficient car concepts for international contests. Besides the engineering work, one part of the project deals with real-time data visualization. In order to increase the efficiency of the vehicle, an online monitoring of the runtime parameters is necessary. The driving parameters of the vehicle are transmitted to a processing station via a wireless network connection. We plan to use an augmented reality (AR) application to visualize different data on top of the view of the real car. By utilizing a mobile Android or iOS device a user can interactively view various real-time and statistical data. The car and its components are meant to be augmented by various additional information, whereby that information should appear at the correct position of the components. An engine e.g. could show the current rpm and consumption values. A battery on the other hand could show the current charge level. The goal of this paper is to evaluate different possible approaches, their suitability and to expand our application to other projects at our university.
Objectives: Speech recognition on the telephone poses a challenge for patients with cochlear implants (CIs) due to a reduced bandwidth of transmission. This trial evaluates a home-based auditory training with telephone-specific filtered speech material to improve sentence recognition. Design: Randomised controlled parallel double-blind. Setting: One tertiary referral centre. Participants: A total of 20 postlingually deafened patients with CIs. Main outcome measures: Primary outcome measure was sentence recognition assessed by a modified version of the Oldenburg Sentence Test filtered to the telephone bandwidth of 0.3-3.4 kHz. Additionally, pure tone thresholds, recognition of monosyllables and subjective hearing benefit were acquired at two separate visits before and after a home-based training period of 10-14 weeks. For training, patients received a CD with speech material, either unmodified for the unfiltered training group or filtered to the telephone bandwidth in the filtered group. Results: Patients in the unfiltered training group achieved an average sentence recognition score of 70.0%±13.6% (mean±SD) before and 73.6%±16.5% after training. Patients in the filtered training group achieved 70.7%±13.8% and 78.9%±7.0%, a statistically significant difference (P=.034, t10 =2.292; two-way RM ANOVA/Bonferroni). An increase in the recognition of monosyllabic words was noted in both groups. The subjective benefit was positive for filtered and negative for unfiltered training. Conclusions: Auditory training with specifically filtered speech material provided an improvement in sentence recognition on the telephone compared to training with unfiltered material.
The ability to detect a target signal masked by noise is improved in normal-hearing listeners when interaural phase differences (IPDs) between the ear signals exist either in the masker or in the signal. To improve binaural hearing in bilaterally implanted cochlear implant (BiCI) users, a coding strategy providing the best possible access to IPDs is highly desirable. Outcomes of a previous study (Zirn, Arndt et al. 2016) revealed that a subset of BiCI users showed improved IPD detection thresholds with the fine structure processing strategy FS4 compared to the constant rate strategy HDCIS using narrowband stimuli. In contrast, little differences between the coding strategies were found for broadband stimuli with regard to binaural speech intelligibility level differences (BILD) as an estimate of binaural unmasking. Compared to normalhearing listeners (7.5 ± 1.2 dB) BILD were small in BiCI users (around 0.5 dB with both coding strategies).
In the present work, we investigated the influence of binaural fitting parameters on BILD. In our cohort of BiCI users many were implanted with electrode arrays differing in length left versus right. Because this length difference typically corresponded to the distance of two electrode contacts the first modification of bilateral fitting was a tonotopic adjustment by deactivation of the most apical electrode contact on the side with the deeper inserted array (tonotopic approach).
The second modification was the isolation of the residual, most apical electrode contacts by deactivation of the basally adjacent electrode contact on each side (tonotopic sparse approach). Applying these modifications, BILD improved by up to 1.5 dB.
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.
In medical applications wireless technologies are not widely spread. Today they are mainly used in non latency-critical applications where reliability can be guaranteed through retransmission protocols and error correction mechanisms. By using retransmission protocols within the disturbed shared wireless channel latency will increase. Therefore retransmission protocols are not sufficient for removing latency-critical wired connections within operating rooms such as foot switches. Todays research aims to improve reliability through the physical characteristics of the wireless channel by using diversity methods and more robust modulation. In this paper an Architecture for building up a reliable network is presented. The Architecture offers the possibility for devices with different reliability, latency and energy consumption requirements to participate. Furthermore reliability, latency and energy consumption are scalable for every single participant.
Economic growth is usually driven by improvements in productivity, economic efficiency, trade and innovation. Increasing efficiency means to produce larger output using the same amount of factors for production such as raw materials, labour, and capital. However, regardless of the driver, growth is often investment-hungry and it is not rare to find an economy with potential for growth but lacking locally available investment. In this scenario, Foreign Direct Investment (FDI) can fill the gap between investment needed to promote economic growth and locally available investments.
Gaps in basic math knowledge are among the biggest obstacles to a successful start in university. Students starting their studies in STEM disciplines display significant diversity, “math anxiety” is a widespread phenomenon, and the transition to a self-determined way of studying presents a huge challenge. Universities offer support measures such as preparatory courses. Over the years, Offenburg University realized that with increased diversity, traditional ways of teaching in front of the class have become inefficient. The majority of the students remained inactive and just listened to the teachers’ explanations and the few active participants’ answers.
Since 2013 our new course concept fosters a shift from teaching to active learning on a large scale, involving several hundred participants of our on-site preparatory math courses. This switch to broad active practicing, however, must go hand in hand with providing individual support for an increasingly diverse student body. Meanwhile students bring along their mobile devices, and the training App TeachMatics serves as a facilitator. The course concept has been very well received by both students and teachers.
In the past two decades much has been published on whiplash injury, yet both the confusion regarding the condition, and the medicolegal discussion about it have increased. In this paper, functional imaging research results are summarized using MRIcroGL3D visualization software and assembled in an image comprising regions of cerebral activation and deactivation.