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This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images.
In der Vergangenheit basierten große Systemintegrationsprojekte in der Regel auf Individualentwicklungen für einzelne Kunden. Getrieben durch Kostendruck steigt aber der Bedarf nach standardisierten Lösungen, die gleichzeitig die individuellen Anforderungen des jeweiligen Umfelds berücksichtigen. T-Systems GEI GmbH wird beiden Anforderungen mit Produktkerneln gerecht. Neben den technischen Aspekten der Kernelentwicklung spielen besonders organisatorische Aspekte eine Rolle, um Kernel effizient und qualitativ hochwertig zu entwickeln, ohne deren Funktionalitäten ins Uferlose wachsen zu lassen. Umgesetzt hat T-Systems dieses Konzept für Flughafeninformationssysteme. Damit kann dem wachsenden Bedarf der Flughafenbetreiber nach einer effizienten und kostengünstigen Softwarelösung zur Unterstützung Ihrer Geschäftsprozesse entsprochen werden.
This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand.
Der Erfolg eines Softwarenentwicklungsprojektes insbesondere eines Systemintegrationsprojektes wird mit der Erfüllung des „Teufelsdreiecks“, „In-Time“, „In-Budget“, „In-Quality“ gemessen. Hierzu ist die Kenntnis der Software- und Prozessqualität essenziell, um die Einhaltung der Qualitätskriterien festzustellen, aber auch, um eine Vorhersage hinsichtlich Termin- und Budgettreue zu treffen. Zu diesem Zweck wurde in der T-Systems Systems Integration ein System aus verschiedenen Key Performance Indikatoren entworfen und in der Organisation implementiert, das genau das leistet und die Kriterien für CMMI Level 3 erfüllt.
In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
This paper introduces a hardware setup to measure efficiency maps of low-power electric motors and their associated inverters. Here, the power of the device under test (DUT) ranges from some Watts to a few hundred Watts. The torque and speed of the DUT are measured independent of voltage and current in multiple load points. A Matlab-based software approach in combination with an open Texas-Instruments (TI) hardware setup ensures flexibility. Exemplarily, the efficiency field of a Permanent Magnet Synchronous Machine (PMSM) is measured to proof the concept. Brushless-DC (BLDC) motors can be tested as well. The nomenclature in this paper is based on the new European standard DIN EN 50598. Special attention is paid to the calculation of the measurement error.
Electromicrobial engineering is an emerging, highly interdisciplinary research area linking bioprocesses with electrochemistry. In this work, microbial electrosynthesis (MES) of biobutanol is carried out during acetone-butanol-ethanol (ABE) fermentations with Clostridium acetobutylicum. A constant electric potential of −600mV (vs. Ag/AgCl) with simultaneous addition of the soluble redox mediator neutral red is used in order to study the electron transfer between the working electrode and the bacterial cells. The results show an earlier initiation of solvent production for all fermentations with applied potential compared to the conventional ABE fermentation. The f inal butanol concentration can be more than doubled by the application of a negative potential combined with addition of neutral red. Moreover a higher biofilm formation on the working electrode compared to control cultivations has been observed. In contrast to previous studies, our results also indicate that direct electron transfer (DET) might be possible with C. acetobutylicum. The presented results make microbial butanol production economically attractive and therefore support the development of sustainable production processes in the chemical industry aspired by the “Centre for resource-efficient chemistry and raw material change” as well as the the project “NanoKat” working on nanostructured catalysts in Kaiserslautern.