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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.
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.
In this experimental work we present a novel electrolyzer system for the production of hydrogen and oxygen at high pressure levels without an additional mechanical compressor. Due to its control strategies, the operation conditions for this electrolyzer can be kept optimal for each load situation of the system. Furthermore, the novel system design allows for dynamic long-term operation as well as for easy maintainability. Therefore, the device meets the requirements for prospective power-to-gas applications, especially, in order to store excess energy from renewable sources. A laboratory scale device has been developed and high-pressure operation was validated. We also studied the long-term stability of the system by applying dynamic load cycles with load changes every 30 sec. After 80 h of operation the used membrane electrode assembly (MEA) was investigated by means of SEM, EDX and XRD analysis.
CoCoSpot: Clustering and recognizing botnet command and control channels using traffic analysis
(2017)
Improved Plasma Membrane Models as Test Systems for the Membrane
Disrupting Activity of Kalata B1
(2017)
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.
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.
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.
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.
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.
Performance enhancing study for large scale PEM electrolyzer cells based on hydraulic compression
(2017)
Adhesive organs enable insects to reversibly adhere to substrates even during rapid locomotion. In this process a very fast but reliable change of adhesion and detachment is realised. The stick insect Carausius morosus detaches its adhesive organs by peeling them off the substrate, meaning little areas of the adhesive organs are detached one after another. For such a detachment mechanism low pulling forces are needed. A detachment mechanism as peeling seems also for artificial adhesion devices to be the easiest and the most effortless mechanism for detachment. However, artificial adhesion devices mostly exhibit a solid backing layer preventing effortless peeling. To lift up and detach a small area at the corner of an adhesion device the backing layer has to be tilted, resulting in a deformation of the whole adhesion device, which requires high forces. Subdividing the backing layer into small subunits allows a detachment of a small area at the corner of the adhesion device without deforming the rest of the adhesion device. Thereby, less force is needed to initiate and to complete detachment. To realise an easy detachment of artificial adhesion devices we constructed a holder, which gradually detaches an adhesion device from two sides off the substrate. During normal loading the subunits of the holder interlock with each other so that the pulling force is equally distributed over the whole contact area of the adhesion device ensuring maximal adhesion force. In addition, the holder can be used to increase adhesion during application of the adhesion device. When brought into contact with the substrate with lifted sides, which are lowered subsequently, air trapping is prevented and hence the area of contact can be maximised.
This experimental work deals with the preparation and investigation of PEM fuel cell electrodes, which are obtained using Graphene Related Material (GRM) serving as catalyst support material for platinum nanoparticles. The applied GRM belong to the group of carbon nanofibers and exhibits a helical-ribbon structure with dimensions of 50 nm in diameter and an average length up to a few µm. Furthermore, utilized GRM provide a superior graphitisation degree of about 100 %, which leads to both high corrosion resistance and low ohmic resistance. Material stability plays one of the main roles for long term fuel cell operation, whereby a great electrical catalyst contact combined with high specific surface area yields in high fuel cell performances.
Prior to GRM dispersion and deposition onto a gas diffusion layer, the graphene structures are functionalized by oxygen plasma treatment. Through this step, functional oxygen groups are generated onto the GRM outer surface providing an improved hydrophilic behaviour and facilitating the GRM suspension preparation. In addition, the oxygen groups act as anchors for platinum nanoparticles which are subsequently deposited onto the GRM surface through a pulse electrodeposition process.
Membrane electrode assemblies produced with the prepared electrodes are investigated in-situ in a PEM fuel cell test bench.
This work deals with the preparation and investigation of PEM fuel cell electrodes, which are obtained using graphene related material (GRM) serving as catalyst support for platinum nanoparticles. Applied GRM are used for the preparation of suspensions in four distinct mixing ratios. Two sorts of GRM have been investigated: carbon nanofibers (CNF) and graphene oxide (GO). Utilized CNFs provide a superior graphitization degree of about 100%, which leads to both high corrosion resistance and low ohmic resistance in PEM fuel cells.
For electrode preparation a GRM containing layer serving as catalyst support is applied onto a gas diffusion layer (GDL). Prior to GRM suspension and deposition onto a GDL, the graphene structures are functionalized by plasma treatment. Due to this step, an improved hydrophilic behavior for facilitating suspension preparation is achieved. In addition, a subsequent platinum nanoparticle deposition by pulsed electrodeposition process is optimized.
For this study gas diffusion electrodes (GDE) with low platinum loading are prepared for the application as anode in polymer electrolyte membrane fuel cell (PEMFC) systems based on hydraulic compression. As catalyst support material, carbon nanofibers (CNF) are investigated because of their high specific surface area and high graphitization degree. The electrode preparation is optimized by an economic and environmental friendly pre-treatment process in oxygen plasma. For GDE manufacture an ink containing oxygen plasma activated CNFs as well as hydrophilic polymer is used. After spray coating of this CNF ink on a graphitic substrate, platinum is deposited using the pulse plating technique. Preliminary results showed a considerable improvement of CNF dispersibility as well as an increased amount and an optimized morphology of the deposited platinum. Morphology and microstructure are observed by scanning electron microscopy as well as transmission electron microscopy. Platinum loading is determined by thermogravimetric analysis to be in the range of 0.01 mg cm-2 to 0.017 mg cm-2. Furthermore, MEAs are prepared from these GDEs and testing is performed in a novel modular fuel cell test stack based on hydraulic compression. Technical information about stack design and functions is given in this work.