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51.
Gian Luigi Angrisani Piriya Taptimthong Susanne Elisabeth Thürer Christian Klose Hans Jürgen Maier Marc Christopher Wurz Kai Möhwald 《Advanced Engineering Materials》2018,20(9)
52.
Raman Scattering Mapping: Sensitive and Reproducible Immunoassay of Multiple Mycotoxins Using Surface‐Enhanced Raman Scattering Mapping on 3D Plasmonic Nanopillar Arrays (Small 39/2018)
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53.
METHOD: The time from first diagnosis of primary multiple metastatic prostate carcinoma until progression and until death in patients less than 60 years old under two different therapeutic regimens was evaluated. RESULTS: In the group with pure androgen deprivation (n = 21), the mean time until progression was 11.3 (6-55) months, the mean survival time being 21.4 (11-75) months. In the group with androgen deprivation plus cytostatic therapy (n = 10), progression was noted after 26.7 (15-77) months with a medium survival time of 26.2 (16-82) months. CONCLUSION: The data argue in favor of changing the usual treatment strategy to combination therapy in "young' patients with primary metastatic prostatic cancer. 相似文献
54.
Even though there is abundant literature on successful cases of organizations applying knowledge management (KM) measures,
many KM initiatives have failed to achieve their knowledge and business goals. In order to foster decisions about the design
of such initiatives, information is required on success factors and barriers when selecting KM measures. Multi agent-based
simulation (MABS) is suggested as instrument to investigate potential effects of KM measures on dependent variables such as
sharing of knowledge in organizations or business performance. For such a simulation, the concept of knowledge sharing, influencing
factors and their impact on business and knowledge goals are modeled based on an extensive multi-disciplinary literature survey.
An extensive domain model is operationalized in a simulation model which is then further simplified and implemented in a MABS
tool used for a series of experiments contrasting results with/without KM measures, specifically skill and experience management.
Skill management is found highly sensitive with respect to conditions of application and has no significant impact on knowledge
or business goals. Experience management positively impacts knowledge and business goals. Personal documentation leads to
specialist, project debriefings to generalist knowledge workers. Finally, the paper discusses the simulation’s limitations
and further areas of application. 相似文献
55.
Nils Hasler Carsten Stoll Bodo Rosenhahn Thorsten Thormhlen Hans-Peter Seidel 《Computers & Graphics》2009,33(3):211
The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans. 相似文献
56.
57.
Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems 总被引:5,自引:0,他引:5
Robert J. May Graeme C. Dandy Holger R. Maier John B. Nixon 《Environmental Modelling & Software》2008,23(10-11):1289-1299
Recent trends in the management of water supply have increased the need for modelling techniques that can provide reliable, efficient, and accurate representation of the complex, non-linear dynamics of water quality within water distribution systems. Statistical models based on artificial neural networks (ANNs) have been found to be highly suited to this application, and offer distinct advantages over more conventional modelling techniques. However, many practitioners utilise somewhat heuristic or ad hoc methods for input variable selection (IVS) during ANN development.This paper describes the application of a newly proposed non-linear IVS algorithm to the development of ANN models to forecast water quality within two water distribution systems. The intention is to reduce the need for arbitrary judgement and extensive trial-and-error during model development. The algorithm utilises the concept of partial mutual information (PMI) to select inputs based on the analysis of relationship strength between inputs and outputs, and between redundant inputs. In comparison with an existing approach, the ANN models developed using the IVS algorithm are found to provide optimal prediction with significantly greater parsimony. Furthermore, the results obtained from the IVS procedure are useful for developing additional insight into the important relationships that exist between water distribution system variables. 相似文献
58.
This article presents a method for classifying color points for automotive applications in the Hue Saturation Intensity (HSI)
Space based on the distances between their projections onto the SI plane. Firstly the HSI Space is analyzed in detail. Secondly
the projection of image points from a typical automotive scene onto the SI plane is shown. The minimal classes relevant for
driver assistance applications are derived. The requirements for the classification of the points into those classes are obtained.
Several weighting functions are proposed and a fast form of an euclidean metric is investigated in detail. In order to improve
the sensitivity of the weighting function, dynamic coefficients are introduced. It is shown how to compute them automatically
in order to get optimal results for the classification. Finally some results of applying the metric to the sample images are
shown and the conclusions are drawn.
Calin Rotaru is a PhD candidate at the Department of Computer Science, University of Hamburg, Germany. His PhD work focuses on the topic color machine vision for driver assistance systems and is supported by Volkswagen AG, Group Research Electronics. He graduated (2002) with the topic “Stereo Camera Based Object Recognition” for Driver Assistance Systems from the Faculty of Automation and Computer Science of the Technical University of Cluj-Napoca, Romania. His research interests include color machine vision, smart vision systems, multisensorial data fusion and vision in driver assistance systems. Thorsten Graf received the diploma (M.Sc.) degree in computer science and the Ph.D. degree (his thesis was on “Flexible Object Recognition Based on Invariant Theory and Agent Technology”) from the University of Bielefeld, Bielefeld, Germany, in 1997 and 2000, respectively. In 1997 he became a Member of the “Task Oriented Communication” graduate program, University of Bielefeld, funded by the German research foundation DFG. In June 2001 he joined Volkswagen Group Research, Wolfsburg, Germany. Since then, he has worked on different projects in the area of driver assistance systems as a Researcher and Project Leader. He is the author or coauthor of more than 40 publications and owns several patents. His research interests include image processing and analysis dedicated to advanced comfort/safety automotive applications. Dr. Jianwei Zhang is full professor and director of the Institute of Technical Aspects of Multimodal Systems, Department of Computer Science, University of Hamburg, Germany. He is one of the Chair Professors “Human-Computer Interaction” of the Department of Computer Science of Tsinghua University. He received his Bachelor (1986) and Master degree (1989) from the Department of Computer Science of Tsinghua University, and his PhD (1994) from the Department of Computer Science, University of Karlsruhe, Germany. His research interests include multimodal information processing, robot learning, service robots, smart vision systems and Embodied Intelligence. In these areas he has published over 120 journal and conference papers, six book chapters and two research monographs. He leads numerous basic research and application projects, including the EU basic research programs and the Collaborative Research Centre supported by the German Research Council. Dr. Zhang has received multiple awards including the IEEE ROMAN Best Paper 2002. 相似文献
Jianwei ZhangEmail: |
Calin Rotaru is a PhD candidate at the Department of Computer Science, University of Hamburg, Germany. His PhD work focuses on the topic color machine vision for driver assistance systems and is supported by Volkswagen AG, Group Research Electronics. He graduated (2002) with the topic “Stereo Camera Based Object Recognition” for Driver Assistance Systems from the Faculty of Automation and Computer Science of the Technical University of Cluj-Napoca, Romania. His research interests include color machine vision, smart vision systems, multisensorial data fusion and vision in driver assistance systems. Thorsten Graf received the diploma (M.Sc.) degree in computer science and the Ph.D. degree (his thesis was on “Flexible Object Recognition Based on Invariant Theory and Agent Technology”) from the University of Bielefeld, Bielefeld, Germany, in 1997 and 2000, respectively. In 1997 he became a Member of the “Task Oriented Communication” graduate program, University of Bielefeld, funded by the German research foundation DFG. In June 2001 he joined Volkswagen Group Research, Wolfsburg, Germany. Since then, he has worked on different projects in the area of driver assistance systems as a Researcher and Project Leader. He is the author or coauthor of more than 40 publications and owns several patents. His research interests include image processing and analysis dedicated to advanced comfort/safety automotive applications. Dr. Jianwei Zhang is full professor and director of the Institute of Technical Aspects of Multimodal Systems, Department of Computer Science, University of Hamburg, Germany. He is one of the Chair Professors “Human-Computer Interaction” of the Department of Computer Science of Tsinghua University. He received his Bachelor (1986) and Master degree (1989) from the Department of Computer Science of Tsinghua University, and his PhD (1994) from the Department of Computer Science, University of Karlsruhe, Germany. His research interests include multimodal information processing, robot learning, service robots, smart vision systems and Embodied Intelligence. In these areas he has published over 120 journal and conference papers, six book chapters and two research monographs. He leads numerous basic research and application projects, including the EU basic research programs and the Collaborative Research Centre supported by the German Research Council. Dr. Zhang has received multiple awards including the IEEE ROMAN Best Paper 2002. 相似文献
59.
Ordered binary decision diagrams are the state-of-the-art representation of switching functions. In order to keep the sizes of OBDDs tractable, heuristics and dynamic reordering algorithms are applied to optimize the underlying variable order. When finite state machines are represented by OBDDs the state encoding can be used as an additional optimization parameter. In this paper, we analyze local encoding transformations which can be applied dynamically. First, we investigate the potential of re-encoding techniques. We then propose the use of an XOR-transformation and show why this transformation is most suitable among the set of all encoding transformations. The presented theoretical framework establishes a new optimization technique for OBDDs. 相似文献
60.
Plate J Holtkaemper T Froehlich B 《IEEE transactions on visualization and computer graphics》2007,13(6):1584-1591
We present a powerful framework for 3D-texture-based rendering of multiple arbitrarily intersecting volumetric datasets. Each volume is represented by a multi-resolution octree-based structure and we use out-of-core techniques to support extremely large volumes. Users define a set of convex polyhedral volume lenses, which may be associated with one or more volumetric datasets. The volumes or the lenses can be interactively moved around while the region inside each lens is rendered using interactively defined multi-volume shaders. Our rendering pipeline splits each lens into multiple convex regions such that each region is homogenous and contains a fixed number of volumes. Each such region is further split by the brick boundaries of the associated octree representations. The resulting puzzle of lens fragments is sorted in front-to-back or back-to-front order using a combination of a view-dependent octree traversal and a GPU-based depth peeling technique. Our current implementation uses slice-based volume rendering and allows interactive roaming through multiple intersecting multi-gigabyte volumes. 相似文献