Refine
Year of publication
- 2015 (92) (remove)
Document Type
- Conference Proceeding (92) (remove)
Keywords
- Algorithm (1)
- BCH codes (1)
- Bernstein coefficients (1)
- Bernstein polynomials (1)
- Biomechanics Laboratory (1)
- Body-movement (1)
- CRCPolynom (1)
- Checkerboard ordering (1)
- Collision avoidance (1)
- Convex optimization (1)
SInCom 2015
(2015)
Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light-weighted microcontroller platform.
A semilinear distributed parameter approach for solenoid valve control including saturation effects
(2015)
In this paper a semilinear parabolic PDE for the control of solenoid valves is presented. The distributed parameter model of the cylinder becomes nonlinear by the inclusion of saturation effects due to the material's B/H-curve. A flatness based solution of the semilinear PDE is shown as well as a convergence proof of its series solution. By numerical simulation results the adaptability of the approach is demonstrated, and differences between the linear and the nonlinear case are discussed. The major contribution of this paper is the inclusion of saturation effects into the magnetic field governing linear diffusion equation, and the development of a flatness based solution for the resulting semilinear PDE as an extension of previous works [1] and [2].
Classification of point clouds by different types of geometric primitives is an essential part in the reconstruction process of CAD geometry. We use support vector machines (SVM) to label patches in point clouds with the class labels tori, ellipsoids, spheres, cones, cylinders or planes. For the classification features based on different geometric properties like point normals, angles, and principal curvatures are used. These geometric features are estimated in the local neighborhood of a point of the point cloud. Computing these geometric features for a random subset of the point cloud yields a feature distribution. Different features are combined for achieving best classification results. To minimize the time consuming training phase of SVMs, the geometric features are first evaluated using linear discriminant analysis (LDA).
LDA and SVM are machine learning approaches that require an initial training phase to allow for a subsequent automatic classification of a new data set. For the training phase point clouds are generated using a simulation of a laser scanning device. Additional noise based on an laser scanner error model is added to the point clouds. The resulting LDA and SVM classifiers are then used to classify geometric primitives in simulated and real laser scanned point clouds.
Compared to other approaches, where all known features are used for classification, we explicitly compare novel against known geometric features to prove their effectiveness.
We present a 3d-laser-scan simulation in virtual
reality for creating synthetic scans of CAD models. Consisting of
the virtual reality head-mounted display Oculus Rift and the
motion controller Razer Hydra our system can be used like
common hand-held 3d laser scanners. It supports scanning of
triangular meshes as well as b-spline tensor product surfaces
based on high performance ray-casting algorithms. While point
clouds of known scanning simulations are missing the man-made
structure, our approach overcomes this problem by imitating
real scanning scenarios. Calculation speed, interactivity and the
resulting realistic point clouds are the benefits of this system.
Reconstruction of hand-held laser scanner data is used in industry primarily for reverse engineering. Traditionally, scanning and reconstruction are separate steps. The operator of the laser scanner has no feedback from the reconstruction results. On-line reconstruction of the CAD geometry allows for such an immediate feedback.
We propose a method for on-line segmentation and reconstruction of CAD geometry from a stream of point data based on means that are updated on-line. These means are combined to define complex local geometric properties, e.g., to radii and center points of spherical regions. Using means of local scores, planar, cylindrical, and spherical segments are detected and extended robustly with region growing. For the on-line computation of the means we use so-called accumulated means. They allow for on-line insertion and removal of values and merging of means. Our results show that this approach can be performed on-line and is robust to noise. We demonstrate that our method reconstructs spherical, cylindrical, and planar segments on real scan data containing typical errors caused by hand-held laser scanners.
Durch den Einsatz von mobilen Endgeräten (z.B. Tablets, Smartphones) erschließen sich immer mehr Möglichkeiten, die Ausführung von Geschäftsprozessen zu unterstützen. Beispielsweise können Geschäftsprozessaktivitäten (z.B. Genehmigung eines Angebots) ortsunabhängig bearbeitet werden, wodurch die Durchlaufzeit signifikant reduziert wird. Die Nutzung von mobilen Apps beschränkt sich hierbei meist nur auf die Unterstützung von effizienter und flexibler Interaktion zwischen den verschiedenen ausführenden Rollen. Dieser Artikel beschreibt, wie mobile Apps nicht nur die Ausführung, sondern auch die Optimierung von Geschäftsprozessen unterstützen können. Hierzu werden vordefinierte Qualitätskriterien kontextabhängig während der Ausführung von Aktivitäten erfasst. Die durch traditionelle Methoden erfassten Daten (z.B. Messung von Kennzahlen) werden somit durch in Echtzeit gesammeltes User Feedback ergänzt. Der Ansatz wird am Beispiel einer eigens entwickelten mobilen App demonstriert und evaluiert.
Domain-specific modelling is increasingly adopted in the software development industry. While open source metamodels like Ecore have a wide impact, they still have some problems. The independent storage of nodes (classes) and edges (references) is currently only possible with complex, specific solutions. Furthermore the developed models are stored in the extensible markup language (XML) data format, which leads to problems with large models in terms of scaling. In this paper we describe an approach that solves the problem of independent classes and references in metamodels and we store the models in the JavaScript Object Notation (JSON) data format to support high scalability. First results of our tests show that the developed approach works and classes and references can be defined independently. In addition, our approach reduces the amount of characters per model by a factor of approximately two compared to Ecore. The entire project is made available as open source under the name MoDiGen. This paper focuses on the description of the metamodel definition in terms of scaling.
Das hier beschriebene und auf einem FPGA vom Typ Spartan-3A DSP realisierte System dient dazu, auf besonders effiziente Weise die Häufigkeitsverteilung nicht erkannter fehlerhafter Nachrichten mit verschiedenen CRCPolynomen
zu berechnen. Damit die Berechnung in möglichst kurzer Zeit stattfindet, wurde das System aus 64 parallel arbeitenden Instanzen von CRC-Findern in mehrstufiger Fließbandorganisation aufgebaut. In der hier beschriebenen Ausbaustufe erreicht das System eine Gesamtleistung von 6,4 ·109 Operationen in der Sekunde.
Technology commercialization is described as the most dreadful challenge for technology-based entrepreneurs. The scarcity of resources and limited managerial experience make it a daunting task, putting in danger the whole firm emergence. Prior research has often build upon the resource-based view to propose that the new firms' performance is dependent on their initial resource endowments and configurations. Nevertheless, little is known on how the early-stage decisions of the entrepreneur might influence on the growth of the firm. Scholars have suggested that both technology and market orientation actions could influence the performance and growth of firms in this context; nevertheless, there is limited empirical evidence of the influence of these different orientations in the context of new technology-based firms (NTBFs). In this study we propose to explore the influence of technology and demand creation actions adopting a demand-side view. We use a longitudinal study on a panel dataset (2004-2007) with 249 U.S. new high-technology firms to test our hypothesis. The results point towards a rather limited influence of initial resource configurations, as well as an unexpected influence of market and technology orientation in the growth dimensions of an NTBF. The research holds implications for the management of new technology-based firms and for those interested in supporting the development of technology entrepreneurship.