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Performance enhancing study for large scale PEM electrolyzer cells based on hydraulic compression
(2017)
This technical report is about the architecture and integration of commercial UAVs in Search and Rescue missions. We describe a framework that consists of heterogeneous UAVs, a UAV task planner, a bridge to the UAVs, an intelligent image hub, and a 3D point cloud generator. A first version of the framework was developed and tested in several training missions in the EU project TRADR.
A compact and efficient PEM electrolyser stack design based on hydraulic single cell compression
(2019)
Neuroscientists want to inspect the data their simulations are producing while these are still running. This will on the one hand save them time waiting for results and therefore insight. On the other, it will allow for more efficient use of CPU time if the simulations are being run on supercomputers. If they had access to the data being generated, neuroscientists could monitor it and take counter-actions, e.g., parameter adjustments, should the simulation deviate too much from in-vivo observations or get stuck.
As a first step toward this goal, we devise an in situ pipeline tailored to the neuroscientific use case. It is capable of recording and transferring simulation data to an analysis/visualization process, while the simulation is still running. The developed libraries are made publicly available as open source projects. We provide a proof-of-concept integration, coupling the neuronal simulator NEST to basic 2D and 3D visualization.
This paper presents a novel approach to build consistent 3D maps for multi robot cooperation in USAR environments. The sensor streams from unmanned aerial vehicles (UAVs) and ground robots (UGV) are fused in one consistent map. The UAV camera data are used to generate 3D point clouds that are fused with the 3D point clouds generated by a rolling 2D laser scanner at the UGV. The registration method is based on the matching of corresponding planar segments that are extracted from the point clouds. Based on the registration, an approach for a globally optimized localization is presented. Apart from the structural information of the point clouds, it is important to mention that no further information is required for the localization. Two examples show the performance of the overall registration.
Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior information on the environment and cannot assume the regular order of man-made environments or meaningful semantic cues. In this work we extensively evaluate different approaches to globally register UGV generated 3D point-cloud data from LiDAR sensors with UAV generated point-cloud maps from vision sensors. The approaches are realizations of different selections for: a) local features: key-points or segments; b) descriptors: FPFH, SHOT, or ESF; and c) transformation estimations: RANSAC or FGR. Additionally, we compare the results against standard approaches like applying ICP after a good prior transformation has been given. The evaluation criteria include the distance which a UGV needs to travel to successfully localize, the registration error, and the computational cost. In this context, we report our findings on effectively performing the task on two new Search and Rescue datasets. Our results have the potential to help the community take informed decisions when registering point-cloud maps from ground robots to those from aerial robots.
A Robust Interface for Head Motion based Control of a Robot Arm using MARG and Visual Sensors
(2018)
Head-controlled human machine interfaces have gained popularity over the past years, especially in the restoration of the autonomy of severely disabled people, like tetraplegics. These interfaces need to be reliable and robust regarding the environmental conditions to guarantee safety of the user and enable a direct interaction between a human and a machine. This paper presents a hybrid MARG and visual sensor system for head orientation estimation which is in this case used to teleoperate a robotic arm. The system contains a Magnetic Angular Rate Gravity (MARG)-sensor and a Tobii eye tracker 4C. A MARG sensor consists of tri-axis accelerometer, gyroscope as well as a magnetometer which enable a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The tri-axis magnetometer is sensitive to external magnetic fields which result in incorrect orientation estimation from the sensor fusion process. In this work the Tobii eye tracker 4C is used to increase head orientation estimation because it also features head tracking even though it is commonly used for eye tracking. This type of visual sensor does not suffer magnetic drift. However, it computes orientation data only, if a user is detectable. Within this work a state machine is presented which enables data fusion of the MARG and visual sensor to improve orientation estimation. The fusion of the orientation data of MARG and visual sensors enables a robust interface, which is immune against external magnetic fields. Therefore, it increases the safety of the human machine interaction.
Opportunities and Challenges in Mixed-Reality for an Inclusive Human-Robot Collaboration Environment
(2018)
This paper presents an approach to enhance robot control using Mixed-Reality. It highlights the opportunities and challenges in the interaction design to achieve a Human-Robot Collaborative environment. In fact, Human-Robot Collaboration is the perfect space for social inclusion. It enables people, who suffer severe physical impairments, to interact with the environment by providing them movement control of an external robotic arm. Now, when discussing about robot control it is important to reduce the visual-split that different input and output modalities carry. Therefore, Mixed-Reality is of particular interest when trying to ease communication between humans and robotic systems.
Steganography, the art of concealing information in different types of medias, is a very old practice. Yet, it only recently started being used by malware operators on a large scale. Malware programmers and operators are increasing their efforts in developing covert communication channels between infected computers and their command and control servers. In addition to steganography, recent examples include hiding communication in inconspicuous network traffic such as DNS queries or HTTP 404 error messages.
When used properly, these covert communication channels can bypass many automated detection mechanisms and render malware communication difficult to detect and block. From an attacker's perspective, covert communication channels are a valuable addition because they allow messages to blend in with legitimate traffic and thus significantly lower the chance of being detected even when inspected by a human analyst.
This presentation studies recent advances in covert communication channels used by real-world malware. First, we will show how steganography has recently been used in three different malware families (Stegoloader, Vawtrak, and Lurk). We will dive into the implementation details on how steganography is implemented and discuss the strengths and weaknesses of each approach. Furthermore, we will detail and compare the usage of inconspicuous carrier protocols for covert communication channels in malware. Examples will span commodity cybercrime as well as targeted attack malware.
The cases that are discussed in this presentation are based on real life incidents. While it is easy to speculate how covert communication channels might be used by malicious actors, documentation of real-world cases is sparse. Yet covert communication channels have arrived in both, the commodity cybercrime and targeted attack world. It is thus vital to understand the status-quo and identify current trends in cybercriminal and targeted attack malware. As such, we believe that it is mandatory to highlight what is currently being used in the wild.
Upgrade of Bioreactor System Providing Physiological Stimuli
to Engineered Musculoskeletal Tissues
(2017)
A novel central control interface (CCI) is developed to improve the modular bioreactor system with regard to extendability and modifiability in Tissue Engineering (TE) applications. This paper presents the results developed in the project with open-source hardware and the graphical programming system LabVIEW. A new platform independent User Interface was further developed to contribute to the new flexibility of the device.
A simplified model for spondylodesis, ie fixation of vertebrae by osteosynthesis, is developed for virtual magnetic resonance imaging (MRI) examinations to numerically calculate energy absorption. This paper presents results of calculated energy absorption in body tissue surrounding titanium rod implants. In general each wire or rod behaves like an antenna in electromagnetic fields. The specific absorption rate (SAR) profile describes dependence of implant size. SAR hotspots appear near the rod edges. Depending of the size of implant fixation SAR is 62%(small fixation) up to 90.95%(large fixation) higher than without implants. In addition, local SAR profile displays local dependency on tissue: SAR is lower between the vertebrae.
Steps Towards an Open All-in-one Rich-Client Environment for Particle-Based Mesoscopic Simulation
(2018)
Renewable and sustainable energy production by many small and distributed producers is revolutionizing the energy landscape as we know it. Consumers produce energy, making them to prosumers in the smart grid. The interaction between prosumers and other entities in the grid and the optimal utilization of new smart grid components (electric cars, freezers, solar panels, etc.) are crucial for the success of the smart grid. The Power Trading Agent Competition is an open simulation platform that allows researchers to conduct low risk studies in this new energy market. In this work we present Maxon16, an autonomous energy broker and champion of the 2016's Power Trading Agent Competition. We present the strategies the broker used in the final round and evaluate the effectiveness of the strategies by analyzing the tournament's results.
Web advertisements are the primary financial source for many online services, but also for cybercriminals. Successful ad campaigns rely on good online profiles of their potential customers. The financial potentials of displaying ads have led to the rise of malware that injects or replaces ads on websites, in particular, so-called adware. This development leads to always further optimized and customized advertising. For these customization's, various tracking methods are used. However, only sparse work has gone into privacy issues emerging from adware. In this paper, we investigate the tracking capabilities and related privacy implications of adware and potentially unwanted programs (PUPs). Therefore, we developed a framework that allows us to analyze any network communication of the Firefox browser on the application level to circumvent encryption like TLS. We use this to dynamically analyze the communication streams of over 16,000 adware or potentially unwanted programs samples that tamper with the users' browser session. Our results indicate that roughly 37% of the requests issued by the analyzed samples contain private information and are accordingly able to track users. Additionally, we analyze which tracking techniques and services are used.
There is a strongly held belief that if companies can direct their marketing activities to improve customer attitudes and intentions, it will impact on purchase behaviors. Departing from complementary yet sometimes conflicting findings of the current literature, we intend to contribute to the literature by answering two related questions. First, we investigate drivers of loyalty intention over time, and by so doing try to better understand loyalty formation. Second, once we understand loyalty formation, we assess the impact of loyalty on different aspects of purchase behavior, considering temporal effects. Therefore, we develop a consumption-system model which assumes that perceptions, intention, and the impact of perceptions and intention on behavior in one period serve as anchors for the same constructs in a subsequent period, implying a pattern of repeated consumption over time.
Using 3SLS regression analysis, results of a large-scale study using survey data from a sample of 2,478 customers from two points in time and purchase data gathered over a 30-month period suggest interesting findings on the two aforementioned questions:
Considering the first question, we find strong support for customer equity drivers directly influencing loyalty. Moreover, we see evidence for loyalty formation as a consumption-system as equity drivers and loyalty intention of one period are significant predictors of the same constructs in the next period.
Addressing the second research question is less straightforward. We find a significant impact of loyalty intention only for purchase frequency, but not for future sales and average receipt. This suggests that in a retailing context, the amount spent depends to a larger extent on actual needs and not on loyalty intention. Loyalty intention seems to be a more appropriate lead indicator for the frequency of store visits. For most categories, repurchase intention will not necessarily be related to higher sales. On the contrary, higher future sales are more likely to depend on the retailer’s ability to cross- and up-sell to its customers. In all, we need to acknowledge that the strongest predictor of future behavior is, in fact, past behavior.
These results question some of the strongly held beliefs of relationship marketing and its impact on actual behavior. Effects might not be as simple as they appear at first, i.e., temporal interplay between constructs. Moreover, it seems that inertia is more important than some marketing research tends to acknowledge. We would therefore suggest a more detailed investigation of customers’ initial choice behavior. If, in fact, inertia is the driving force behind purchase behavior, companies need to augment their emphasis on increasing initial customer contact and, accordingly, on initial product trial. This is somewhat counter-intuitive from a relationship marketing perspective, because that stream of research largely suggests the advantage of retaining customers rather than acquiring new ones. While we are not denying the importance of customer retention, it seems that companies are already fairly successful in doing so – the strong inertia effect confirms that. Hence, customer retention might not be the best strategy to differentiate in the market. Perhaps companies can better differentiate by excelling in customer acquisition. This, however, would have a significant impact on how marketing budgets should be spent by companies trying to reach sustained success. It might be time for re-balancing customer acquisition and customer retention.
Broadening the Target Group for Higher education in Germany: A Case Study on Diversity Management
(2011)
In some industrialized German areas, as in the Ruhr-Area, the percentage of students with migrant background in primary education has overcome the 50 percentage limit with an increasing share in future, the overwhelming part of them with family from Turkey. A large share of those students attains the admission qualification to higher education from “Berufskollegs”, schools which focus on the combination of vocational skills and theoretical education. This migrant potential can primarily be tapped for additional students by universities of applied sciences which are embedded into their regions and dedicated to teaching.
First, we show the approach to conceptualize culture and cultural specifics of migrants with Turkish background this project is based on.
Second, we give an overview on the main actions of the project, systematically presented as a process leading students through the institution (“input, throughput, output”).
Third, we frame the project by referring to principles of diversity management in general.
Diversity Management - an approach to use people of different ages as a resource in enterprises
(2003)
Segmentation of radio-angiographic images using morphological filters, thinning and region growing
(1997)