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Seiffert U.,Fraunhofer Institute for Factory Operation and Automation
Neurocomputing | Year: 2014

Data and especially image compression is becoming increasingly important for efficient resource utilization. Many digital image file formats therefore include universally usable compression methods. They treat every image separately and do not profit from a larger image data set's similar image contents, which are present in numerous biomedical applications. This situation provided the impetus to develop and implement a technical system that incorporates a priori information on typical image contents in image compression on the basis of artificial neural networks and thus increases compression performance for larger image data sets with frequently recurring image contents. © 2013 Elsevier B.V. Source


Naumann A.,Fraunhofer Institute for Factory Operation and Automation | Bielchev I.,Otto Von Guericke University of Magdeburg | Voropai N.,Irkutsk State University | Styczynski Z.,Otto Von Guericke University of Magdeburg
Control Engineering Practice | Year: 2014

An overview of basic IEC standards for smart grid applications is given and some examples of feasible information and communication technology for smart energy systems are shown. As ICT key standards for power grid automation, the two core standards IEC 61850 and IEC 61970 are presented in the paper. Protection automation relying on smart grid ICT technology is shown, and the hurdles to be overcome for the realization of smart grid automation are discussed. Practical examples for are demonstrated. One approach of making different standards work together is presented, which today is still not sufficiently solved and is a main hurdle on the way towards a seamless smart grid automation system. © 2013 Elsevier Ltd. Source


Sreenivasulu N.,Leibniz Institute of Plant Genetics and Crop Plant Research | Borisjuk L.,Leibniz Institute of Plant Genetics and Crop Plant Research | Junker B.H.,Leibniz Institute of Plant Genetics and Crop Plant Research | Mock H.-P.,Leibniz Institute of Plant Genetics and Crop Plant Research | And 4 more authors.
International Review of Cell and Molecular Biology | Year: 2010

Seeds are complex structures composed of several maternal and filial tissues which undergo rapid changes during development. In this review, the barley grain is taken as a cereal seed model. Following a brief description of the developing grain, recent progress in grain development modeling is described. 3-D/4-D models based on histological sections or nondestructive NMR measurements can be used to integrate a variety of datasets. Extensive transcriptome data are taken as a frame to augment our understanding of various molecular-physiological processes. Discussed are maternal influences on grain development and the role of different tissues (pericarp, nucellus, nucellar projection, endosperm, endosperm transfer cells). Programmed cell death (PCD) is taken to pinpoint tissue specificities and the importance of remobilization processes for grain development. Transcriptome data have also been used to derive transcriptional networks underlying differentiation and maturation in endosperm and embryo. They suggest that the "maturation hormone" ABA is important also in early grain development. Massive storage product synthesis during maturation is dependent on sufficient energy, which can only be provided by specific metabolic adaptations due to severe oxygen deficiencies within the seed. To integrate the great variety of data from different research areas in complex, predictive computational modeling as part of a systems biology approach is an important challenge of the future. First attempts of modeling barley grain metabolism are summarized. © 2010 Elsevier Inc. Source


Blumel E.,Fraunhofer Institute for Factory Operation and Automation
Procedia Computer Science | Year: 2013

Effective applied research is based on close collaboration between research and industry, which, taking the findings of basic research on customer demands as its starting point, creates new means to develop and market innovative products. What is more, growing demands for innovative and sustainable results of research and development are prompting the examination of global trends such as demographic change, growing megacities, rising energy consumption and increasing traffic and the resultant social challenges. These trends and increasing traffic in particular are giving rise to new fields of work, especially for digital technologies, as a social responsibility, e.g. on driver assistance and traffic control systems that increase safety. The social challenges are increasingly affecting markets and requiring new innovative products, efficient production processes and integrative forms of human resource development and training and qualification. The virtualization and digitization of objects and processes is becoming an enabler of the development of new strategies and concepts such as smart cities, green energy, electric vehicle networks, smart manufacturing and smart logistics. This paper examines means by which digital engineering and virtual and augmented reality technologies can support the creation of sustainable smart manufacturing and smart logistics processes as well as on-the-job training and qualification and knowledge transfer. © 2013 The Authors. Published by Elsevier B.V. Source


Heinke D.,University of Birmingham | Backhaus A.,Fraunhofer Institute for Factory Operation and Automation
Cognitive Computation | Year: 2011

In earlier work, we developed the Selective Attention for Identification Model (SAIM [16]). SAIM models the human ability to perform translation-invariant object identification in multiple object scenes. SAIM suggests that central for this ability is an interaction between parallel competitive processes in a selection stage and a object identification stage. In this paper, we applied the model to visual search experiments involving simple lines and letters. We presented successful simulation results for asymmetric and symmetric searches and for the influence of background line orientations. Search asymmetry refers to changes in search performance when the roles of target item and non-target item (distractor) are swapped. In line with other models of visual search, the results suggest that a large part of the empirical evidence can be explained by competitive processes in the brain, which are modulated by the similarity between target and distractor. The simulations also suggest that another important factor is the feature properties of distractors. Finally, the simulations indicate that search asymmetries can be the outcome of interactions between top-down (knowledge about search items) and bottom-up (feature of search items) processing. This interaction in VS-SAIM is dominated by a novel mechanism, the knowledge-based on-centre-off-surround receptive field. This receptive field is reminiscent of the classical receptive fields but the exact shape is modulated by both, top-down and bottom-up processes. The paper discusses supporting evidence for the existence of this novel concept. © 2010 The Author(s). Source

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