Major development challenges in application of hydrogenated amorphous silicon (a-Si:H) technology to large area digital X-ray imaging and technological attributes such as low temperature deposition and high uniformity...
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Durch Proteasen ausgelöste Nanopartikelselbstorganisation diente zum Aufbau multimerer Assoziate mit neuen Eigenschaften. In ihrer Zuschrift auf S. 3233 ff. zeigen S. N. Bhatia et al., dass das Binden komplement&...
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Durch Proteasen ausgelöste Nanopartikelselbstorganisation diente zum Aufbau multimerer Assoziate mit neuen Eigenschaften. In ihrer Zuschrift auf S. 3233 ff. zeigen S. N. Bhatia et al., dass das Binden komplementärer Fe 3 O 4 ‐Nanopartikel durch das Anbinden von Polymeren inhibiert wird. Das Nanopartikel bleibt in seinem “Ruhezustand”, bis eine Protease seine Selbstorganisation auslöst.
This paper presents an analysis of the applicability of Sparse Kernel Principal Component Analysis (SKPCA) for feature extraction in speech recognition, as well as, a proposed approach to make the SKPCA technique real...
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Heteroepitaxial growth of SiGe on thin Si membranes leads to the sharing of the epitaxial strain between the Si template layer and the deposited thin film. At high Ge concentrations, at which Ge forms dislocation-free...
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Heteroepitaxial growth of SiGe on thin Si membranes leads to the sharing of the epitaxial strain between the Si template layer and the deposited thin film. At high Ge concentrations, at which Ge forms dislocation-free hut nanostructures, there can be significant bending underneath self-assembled Ge huts. We have fabricated undercut mesas to approximate a freestanding Si membrane and produced Ge hut structures using molecular beam epitaxy. Using synchrotron x-ray microdiffraction to probe the strain and bending of the template layer directly, we compare strain sharing in conventional blanket film structures with the strain induced by Ge hut structures.
The stringent requirements on size and power consumption constrain the conventional hearing aid devices from providing the patients an economic and user friendly solution, specifically for better noise cancellation. W...
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Sterically shielded …︁ …︁ nanoparticles diffuse freely in solution and biological fluids until proteases expressed by cancer cells trigger them to self-assemble. In their Communication on page 3161ff., S. N. Bhatia ...
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Sterically shielded …︁ …︁ nanoparticles diffuse freely in solution and biological fluids until proteases expressed by cancer cells trigger them to self-assemble. In their Communication on page 3161ff., S. N. Bhatia and co-workers show that complimentary Fe 3 O 4 nanoparticle binding is inhibited by the attachment of protease-cleavable polymers. Cleavage of these polymers triggers “latent” nanoparticles to form multimeric assemblies with emergent properties.
To develop software for embedded systems the designer must take into account different kinds of problems and complexities. The main issues are related to late integration with the target hardware and the separation of...
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Most edge detection algorithms include three main stages: smoothing, differentiation, and labeling. In this paper, we evaluate the performance of algorithms in which competitive learning is applied first to enhance ed...
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ISBN:
(纸本)1604238216
Most edge detection algorithms include three main stages: smoothing, differentiation, and labeling. In this paper, we evaluate the performance of algorithms in which competitive learning is applied first to enhance edges, followed by an edge detector to locate the edges. In this way, more detailed and relatively more unbroken edges can be found as compared to the results when an edge detector is applied alone. The algorithms compared are K-Means, SOM and SOGR for clustering, and Canny and GED for edge detection. Perceptionally, best results were obtained with the GED-SOGR algorithm. The SOGR is also considerably simpler and faster than the SOM algorithm.
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi;yi) a distribution over (xi;y i) is specified. In partic...
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ISBN:
(纸本)0262195348
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi;yi) a distribution over (xi;y i) is specified. In particular, we derive a robust formulation when the distribution is given by a normal distribution. It leads to Second Order Cone programming formulation. Our method is applied to the problem of missing data, where it outperforms direct imputation.
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