Information Theoretic Deformable Registration Using Local Image Information

We present a deformable registration algorithm for multi-modality images based on information theoretic similarity measures at the scale of individual image voxels. We derive analytical expressions for the mutual information, the joint entropy, and the sum of marginal entropies of two images over a small neighborhood in terms of image gradients. Using these expressions, we formulate image registration algorithms maximizing local similarity over the whole image domain in an energy minimization framework. This strategy produces highly elastic image alignment as the registration is driven by voxel similarities between the images, the algorithms are easily implementable using the closed-form expressions for the derivative of the optimization function with respect to the deformation, and avoid estimation of joint and marginal probability densities governing the image intensities essential to conventional information theoretic image registration methods. This work has been supported in part by NIH grants R01-NS42645 and R01-AG14971.     

Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets

Decision making is one of the most complex administrative processes in management. In circumstances where the members of the decision making team are uncertain in determining and defining the decision making criteria, fuzzy theory provides a proper tool to encounter with such uncertainties. However, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, the interval-valued fuzzy set theory can provide a more accurate modeling. In this paper the interval-valued fuzzy TOPSIS method is presented aiming at solving MCDM problems in which the weights of criteria are unequal, using interval-valued fuzzy sets concepts.     

Interactive search and browsing interface for large-scale visual repositories

Due to the rapid proliferation of both user-generated and broadcasted content, the interfaces for search and browsing of visual media have become increasingly important. This paper presents a novel intuitive interactive interface for browsing of large-scale image and video collections. It visualises underlying structure of the dataset by the size and spatial relations of displayed images. In order to achieve this, images or video key-frames are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images that are hierarchically laid out on the screen, user can intuitively navigate through the collection or search for specific content. The extensive experimental results based on user evaluation of photo search, browsing and selection as well as interactive video search demonstrate good usability of the presented system and improvement when compared to the standard methods for interaction with large-scale image and video collections.     

Noise Reduction in Surface Reconstruction from a Given Gradient Field

We present a gradient space technique for noise reduction in surfaces reconstructed from a noisy gradient field. We first analyze the error sources in the recovered gradient field of a surface using a three-image photometric stereo method. Based on this analysis, we propose an additive noise model to describe the errors in the surface gradient estimates. We then use a vector space formulation and construct a multiscale orthonormal expansion for gradient fields. Using the sparse representation properties of this expansion, we develop techniques for reducing the gradient field noise by coefficient selection with thresholding. The simulation results indicate that the proposed technique provides significant improvement on the noise levels of both the estimated gradient fields and the reconstructed surfaces under heavy noise levels. Furthermore, the experiments using noisy photometric stereo image triplets of real range data suggest that the additive model remains viable after the nonlinear photometric stereo operation to provide accurate noise removal.     

Quantum Gas of Polar Molecules Ensembles at Ultralow Temperatures: <Emphasis Type="Italic">f</Emphasis>-wave Superfluids

We investigate novel f-wave superfluids of fermionic polar molecules in a two-dimensional bilayer system with dipole moments polarized perpendicular to the layers and in opposite directions in different layers. The solution of the BCS gap equation reveals that these unconventional superfluids emerge at temperatures on the level of femtokelvin which opens up new possibilities to explore the topological \(f+i f\) phase, quantum interferometry and Majorana fermions in experiments with ultracold polar molecules. The experimental realization of such interesting novel f-wave pairings is discussed.     

Evolutionary and Genetic Algorithms Applied to Li<Superscript>+</Superscript>-C System: Calculations Using Differential Evolution and Particle Swarm Algorithm

A set of empirical potentials based upon two and three body interactions were constructed for the Li⁺-C system and structural optimizations for various assemblages containing Li⁺ ions and graphene sheets were conducted using some emerging evolutionary and genetic algorithms, differential evolution, and particle swarm optimization in particular. Some limited molecular dynamics calculations were also performed. The results are discussed and analyzed with reference to the lithium ion batteries, where the graphite-Li⁺ assemblages traditionally constitute the negative electrode, for which the present results are highly pertinent.

Adaptive delivery of immersive 3D multi-view video over the Internet

The increase in Internet bandwidth and the developments in 3D video technology have paved the way for the delivery of 3D Multi-View Video (MVV) over the Internet. However, large amounts of data and dynamic network conditions result in frequent network congestion, which may prevent video packets from being delivered on time. As a consequence, the 3D video experience may well be degraded unless content-aware precautionary mechanisms and adaptation methods are deployed. In this work, a novel adaptive MVV streaming method is introduced which addresses the future generation 3D immersive MVV experiences with multi-view displays. When the user experiences network congestion, making it necessary to perform adaptation, the rate-distortion optimum set of views that are pre-determined by the server, are truncated from the delivered MVV streams. In order to maintain high Quality of Experience (QoE) service during the frequent network congestion, the proposed method involves the calculation of low-overhead additional metadata that is delivered to the client. The proposed adaptive 3D MVV streaming solution is tested using the MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) standard. Both extensive objective and subjective evaluations are presented, showing that the proposed method provides significant quality enhancement under the adverse network conditions.     

Estimating topology preserving and smooth displacement fields

We propose a method for enforcing topology preservation and smoothness onto a given displacement field. We first analyze the conditions for topology preservation on two- and three-dimensional displacement fields over a discrete rectangular grid. We then pose the problem of finding the closest topology preserving displacement field in terms of its complete set of gradients, which we later solve using a cyclic projections framework. Adaptive smoothing of a displacement field is then formulated as an extension of topology preservation, via constraints imposed on the Jacobian of the displacement field. The simulation results indicate that this technique is a fast and reliable method to estimate a topology preserving displacement field from a noisy observation that does not necessarily preserve topology. They also show that the proposed smoothing method can render morphometric analysis methods that are based on displacement field of shape transformations more robust to noise without removing important morphologic characteristics.     

Development of polyester and polyamide conductive fibre

Conducting polyester PET and polyamide PA-6 fibre and fabrics were prepared by in-situ chemical oxidative polymerisation using super critical fluid assisted process. The fibre materials and cloths produced were characterized by means of FTIR, WAXD, SEM, and DSC and two-probe resistivity. The samples were studied also by means of washing them several times. Homogeneous treated fibre materials with sustainable properties were produced. Melt spun fibre material of inherently conducting polymer blends have been reported earlier. Reasonable mechanical and electrical properties (resistance of 10⁵…10⁷ Ω/cm) are typical for blend of polypropylene and polyaniline. With bi-component extrusion technology the fibre as good as 10³…10⁵ Ω/cm is reachable.