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In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.
Die transurethrale Resektion der Prostata (TUR-P) ist der Gold Standard für die endoskopisch-chirurgische Behandlung der Benignen Prostatahyperplasie (BPH). Unbekannt ist jedoch, ob bei der bipolaren TUR-P die Möglichkeit von elektrothermischen Verletzung von benachbar-
tem nichtopertiertem Gewebe besteht. Grund hierfür könnten höhere Ausgangsleistungen der Chirurgie-Generatoren sein. Deshalb werden experimentell gemessene Werte der räumlichen Verlustleistungsdichte um ein bipolares Resektoskop als Quellterm für die Berechnung der Temperaturänderung im operationsnahen Gewebe verwendet. Die Temperaturberechnung basiert auf der numerischen Lösung der Wärmeleitungsgleichung nach Penne. Für die gewählten Randbedingungen und Eingabeparameter sind keine signifikanten Temperaturerhöhungen im Berechnungsgebiet am proximalen Ende des Resektoskop-Schaftes festzustellen. Um ein umfassendes Verständnis zu gewinnen sollen weiterführende Untersuchungen mit einer Variation der Randbedingungen und Eingabeparameter durchgeführt werden.
The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, interoperability and accessibility. Although not new, virtualization and automation are core features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
It is common to have a large noise and/or a strong interference around the frequency band of a Power Line Communication (PLC) system due to the fact that the PLC channel is not designed for communication. If there are no efficient operations at the receiver to suppress this out-of-band noise and interference to some extent, the Signal-to-Noise Ratio (SNR) will decrease and system will suffer performance loss consequently. Normally, the effort of Analog Front End (AFE) on the suppression of out-of-band interference is finite and it is uneconomic to change the AFE structure to make a performance improvement. Therefore, an appropriate structure of Digital Front End (DFE) at the receiver is necessary to reduce the impact of out-of-band noise and interference furthermore. In this paper, three different kinds of DFE structure at the receiver are introduced: classic DFE, time domain Nyquist windowing and Equivalent Complex Baseband (ECB) approach. The performance of these DFE structures is compared, not only from the aspect of out-of-band suppression, but also from the system overhead they need.
In recent years, hardware for the production and consumption of virtual reality content has reached level of prices that make it affordable to everyone. Accordingly schools and universities are showing increased interest in implementations of virtual reality technologies for supporting their innovative educational activities. Hence, this paper presents a flexible architecture for supporting the development of virtual reality learning scenarios conveniently deployed for educational purposes. We also suggest an example of such
educational scenario for medical purposes deployable with the suggested architecture. In addition, we developed and used a questionnaire answered by 17 medical students in order to derive additional requirements for refining such scenarios. Then, we present these efforts while aiming at deployments usable also for additional domains. Finally, we summarize and mention aspects we will address
in our coming efforts while deploying such activities.
In this paper we describe an architecture for behavioral organization based on dynamical systems. This architecture
enables the generation of complex behavioral sequences, which is demonstrated using the example of approaching and
passing a door. The behavioral sequence is generated by activating and deactivating the elementary behaviors dependent
on sensory information and internal logical conditions. The architecture is demonstrated on a mobile KOALA robot and
in simulation as well.
In the field of magnetic inductance tomography,
signal processing is a real challenge. This is due to the divergent
nature of magnetic fields. The sensitivity, i.e. the change in the
receiving signal by means of an electrically conductive sample
in a measuring volume depends strongly on the positioning
of the sample. Objects that are located near the transmitting
or receiving coils are very well locatable, where objects in
larger distance are hard to detect. In this paper an approach
is presented that improves the topology of the magnetic fields
in the ”magnetic induction tomography” (MIT) by changing
geometric constructions and current patterns of coils so far,
as to allow a sharper localization of objects within the space.
The aim is to level the distribution of the sensitivity in the
measuring volume, so that electrically conductive objects with
a larger distance between transmitting and receiving unit can
be detected with almost the same signal intensity as objects
close to the transmitting and receiving unit. The simulation tool
Comsolic is used for the geometric modeling making a finite
element analysis (FEA). The subsequent signal processing and
analysis of the simulation results are implemented in Matlabic .
Within this FEA the coil geometries and current patterns are
changed numerically, so that the minimum object size, that is
still detectable, is, compared to the known MIT, reduced and the
sensitivity of the system is improved. To validate the simulation in
Comsolic , first simulation results are compared with analytical
models and analyses.
The astronomy domain provides rich opportunities for learning about natural phenomena. It can involve and motivate a variety of mathematical and physical knowledge and skills. However it is difficult to connect astronomic observations to modelling and calculation tools and to embed them into educational scenarios. It is particularly this challenge which is focused in this paper. Concretely, we build on an existing collaborative modelling framework (Cool Modes) and extend it with specific representations to support learning activities in astronomy. A first field test has been conducted with these extensions.
Der Einsatz von virtuellen Servern im LDS NRW erfolgte bisher unter dem Blickwinkel der Konsolidierung von einfachen und sehr einfachen Systemen, die keine dedizierte Serversystemtechnik benötigten.
Mittlerweile bietet VMware Funktionalitäten, die neben dem Konsolidierungsgedanken hoch interessante Möglichkeiten für vielfältigste, individuelle Kundenanforderungen bieten. Dies reicht von flexiblen, preiswerten und einfachen
Systemen bis hin zu Serverplattformen mit hohen Ansprüchen an Performance und Verfügbarkeit.
This contribution demonstrates the efficient embedding of a single depth-camera into the automotive environment making mid-air gesture interaction for mobile applications viable in such a scenario. In this setting a new human-machine interface is implemented to give an idea of future improvements in automation processes in industrial applications. Our system is based on a data-driven approach by learning hand poses as well as gestures from a large database in order to apply them on mobile devices. We register any movement in a nearby driver area and crop data efficiently with the means of PCA transforming it into so-called feature vectors which present the input for our multi-layer perceptrons (MLPs). After MLP classification, the interpretation of user input is sent via WiFi to a tablet PC mounted into the car interior visualizing an infotainment system which the user is able to interact with. We demonstrate that by this setup hand gestures as well as hand poses are easily and efficiently interpretable insofar as that they become an intuitive and supplementary means of interaction for automotive HMI in mobile scenarios realizable in real-time.
In recent years, the number of reasonable powerful mobile devices increased. In 2011, the number of smartphones(e.g.)increased to more than 300 million units. A lot of research has already been conducted with respect of mobile devices acting as Cloud Service consumers, but
still not much effort is put on mobile devices in the role of Cloud Service providers. Therefore, this paper presents an approach that allows to utilize mobile devices like smart phones or tablets as Cloud Service providers. In order to make this a reasonable approach, some of the occurring problems are discussed and it is shown how the presented architecture is able to overcome these problems. Last
but not least, this paper
describes some performance
tests of the chosen implementa
tion for mobile Web Services.
CORA is a robotic assistant whose task is to collaborate with a human operator on simple manipulation or handling tasks. Its sensory channels comprising vision, audition, haptics, and force sensing are used to extract perceptual information about speech, gestures and gaze of the operator, and object recognition. The anthropomorphic robot arm makes goal-directed movements to pick up and hand over objects. The human operator may mechanically interact with the arm by pushing it away (haptics) or by taking an object out of the robot's gripper (force sensing). The design objective has been to exploit the human operator's intuition by modeling the mechanical structure, the senses, and the behaviors of the assistant on human anatomy, human perception, and human motor behavior.
We extend the attractor dynamics approach to generate goal-directed movement of a redundant, anthropomorphic arm while avoiding dynamic obstacles and respecting joint limits. To make the robot's movements human-like, we generate approximately straight-line trajectories by using two heading direction angles of the tool-point quite analogously to how movement is represented in the primate central nervous system. Two additional angles control the tool's spatial orientation so that it follows the tool-point's collision-free path. A fifth equation governs the redundancy angle, which controls the elevation of the elbow so as to avoid obstacles and respect joint limits. These variables make it possible to generate movement while sitting in an attractor (or, in the language of the potential field approach, in a minimum). We demonstrate the approach on an assistant robot, which interacts with human users in a shared workspace
The presented work formulates an framework in which early prediction of drivers lane change behavior is realized. We aim to build a representation of drivers lane change behavior in order to recognize and to predict driver's intentions as a first step towards a realistic driver model. In the test bed of the Institute of Neuroinformatik, based on the traffic simulator NISYS TRS 1, 10 individuals have driven in the experiments and they performed more then 150 lane change maneuvers. Lane-offset, distance to the front car and time to contact, were recorded. The acquired data was used to train - in parallel- a recurrent neural network, a feed forward neural network and a set of support vector machines. In the followed test drives the system was able of performing a lane change prediction time of 1.5 sec beforehand. The proposed approach describes a framework for lane-change detection and prediction, which will serve as a prerequisite for a successful driver model.
Generating collision free reaching movements for redundant manipulators using dynamical systems
(2010)
For autonomous robots to manipulate objects in unknown environments, they must be able to move their arms without colliding with nearby objects, other agents or humans. The simultaneous avoidance of multiple obstacles in real time by all link segments of a manipulator is still a hard task both in practice and in theory. We present a systematic scheme for the generation of collision free movements for redundant manipulators in scenes with arbitrarily many obstacles. Based on the dynamical systems approach to robotics, constraints are formulated as contributions to a dynamical system that erect attractors for targets and repellors for obstacles. These contributions are formulated in terms of variables relevant to each constraint and then transformed into vector fields over the manipulator joint velocity vector as an embedding space in which all constraints are simultaneously observed. We demonstrate the feasibility of the approach by implementing it on a real anthropomorphic 8-degrees-of-freedom redundant manipulator. In addition, performance is characterized by detecting failures in a systematic simulation experiment in randomized scenes with varying numbers of obstacles.