Tensor scale: An analytic approach with efficient computation and applications

Scale is a widely used notion in computer vision and image understanding that evolved in the form of scale-space theory where the key idea is to represent and analyze an image at various resolutions. Recently, we introduced a notion of local morphometric scale referred to as “tensor scale” using an ellipsoidal model that yields a unified representation of structure size, orientation and anisotropy. In the previous work, tensor scale was described using a 2-D algorithmic approach and a precise analytic definition was missing. Also, the application of tensor scale in 3-D using the previous framework is not practical due to high computational complexity. In this paper, an analytic definition of tensor scale is formulated for n-dimensional (n-D) images that captures local structure size, orientation and anisotropy. Also, an efficient computational solution in 2- and 3-D using several novel differential geometric approaches is presented and the accuracy of results is experimentally examined. Also, a matrix representation of tensor scale is derived facilitating several operations including tensor field smoothing to capture larger contextual knowledge. Finally, the applications of tensor scale in image filtering and n-linear interpolation are presented and the performance of their results is examined in comparison with respective state-of-art methods. Specifically, the performance of tensor scale based image filtering is compared with gradient and Weickert’s structure tensor based diffusive filtering algorithms. Also, the performance of tensor scale based n-linear interpolation is evaluated in comparison with standard n-linear and windowed-sinc interpolation methods.     

Ante- and perinatal factors and child characteristics predicting parenting experience among formerly infertile couples during the child's first year: A controlled study.

In this prospective controlled study, the authors examined (a) parenting experiences among couples with successful assisted reproduction treatment (ART; n = 367) and fertile spontaneously conceiving controls (n = 371) and (b) the impact of ante- and perinatal factors and child characteristics on parenting experiences. The results show that positive mothering experiences increased more during the 1st year of parenting and were generally higher among ART mothers than control mothers. No differences were found between ART fathers and controls in their fathering experience. Unpleasant birth experiences, low birth weight, and difficulty soothing the child were associated with high levels of parental stress in the control group, but this was not so among the ART parents. Psychosocial interventions in maternal care should take into account the various meanings that couples give to the history of infertility and conception and ante- and perinatal experiences. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Vectorial scale-based fuzzy-connected image segmentation

This paper presents an extension of previously published theory and algorithms for fuzzy-connected image segmentation. In this approach, a strength of connectedness is assigned to every pair of image elements. This is done by finding the strongest among all possible connecting paths between the two elements in each pair. The strength assigned to a particular path is defined as the weakest affinity between successive pairs of elements along the path. Affinity specifies the degree to which elements hang together locally in the image. A scale is determined at every element in the image that indicates the size of the largest homogeneous hyperball region centered at the element. In determining affinity between any two elements, all elements within their scale regions are considered. This method has been effectively utilized in several medical applications. In this paper, we generalize this method from scalar images to vectorial images. In a vectorial image, scale is defined as the radius of the largest hyperball contained in the same homogeneous region under a predefined condition of homogeneity of the image vector field. Two different components of affinity, namely homogeneity-based affinity and object-feature-based affinity, are devised in a fully vectorial manner. The original relative fuzzy connectedness algorithm is utilized to delineate a specified object via a competing strategy among multiple objects. We have presented several studies to evaluate the performance of this method based on simulated MR images, 20 clinical MR images, and 250 mathematical phantom images. These studies indicate that the fully vectorial fuzzy connectedness formulation has generally overall better accuracy than the method using some intermediate ad hoc steps to fit the vectorial image to a scalar fuzzy connectedness formulation, and precision and efficiency are similar for these two methods.     

Highly active recyclable SBA-15-EDTA-Pd catalyst for Mizoroki-Heck,Stille and Kumada C–C coupling reactions

Highly efficient SBA-15-EDTA-Pd(11) heterogeneous catalyst was synthesized by covalent anchoring Pd-EDTA complex over organo-modified surface of SBA-15. SBA-15-EDTA-Pd(11) catalyst was found to exhibit excellent catalytic activity in appreciable yield for Heck, Stille and Kumada cross-coupling reactions. Catalytic system exhibited excellent activity for completion of reaction, isolation, Pd loading (0.87 mmol%) and yields of products as compared to earlier reported heterogeneous supported Pd catalysts. Covalently anchored heterogeneous SBA-15-EDTA-Pd(11) catalyst can be recycled for more than five times without noticeable loss in activity and selectivity.     

Modulations in structural and ferroelectric properties due to tensile strain in BiFeO3 films on MgAl2O4 substrates induced by thermal-expansion

The effect of tensile strain on structural and ferroelectric properties of BiFeO₃ epitaxial films was investigated. The films grown by pulsed laser deposition on MgAl₂O₄ (0 0 1) substrates revealed monoclinic structure deviated from the bulk rhombohedral structure due to a tensile strain along the in-plane direction. The strain is induced by the difference in thermal expansion coefficients between the film and the substrate. A Poisson ratio is calculated from the in-plain and out-of-plain lattice constants at different temperatures measured by reciprocal space maps of X-ray diffraction. The small Poisson ratio compared to the bulk suggests a weaker elastic response at high temperature. The ferroelectric polarization of the tensile-strained film along the (0 0 1) is also decreased from the bulk value.     

Formulae for determining heterodyne system spurious frequencies that coincide with desired output frequency

In this paper, formulae to determine the lowest order and other higher order spurious frequencies that coincide with desired output signal frequencies of mixers have been derived. The proposed formulae give general expressions that are suitable for any order of heterodyne mixing. The formulae have been verified using a suitable example and compared with the simulation results obtained through the radio frequency simulation software of Advanced Design System. The formulae directly reveal the order of the troublesome spurious frequencies that the designers would encounter in heterodyne systems. In comparison with these direct formulae, the results of existing spurious analysis software are based on the maximum order of simulation carried out. Based on these simulations, the coinciding spurious components have to be manually sorted out. Proposed formulae are quick tools used by the microwave system and circuit designers for choosing and finalizing heterodyne frequencies in their designs without the need for any simulations.     

Multi-class blind steganalysis using deep residual networks

Multimedia Tools and Applications - Camouflaged communication using a media is known as Steganography. It is different than encryption as the presence of message is also concealed in case of...     

Trust-based access control for collaborative systems

In distributed, heterogeneous and network-connected collaborative environments where resources are provided to diverse unknown users for their applications, it is necessary to define access control for resources. Access control for such systems is defined as the ability to authorise or repudiate access to resources by a particular user. Traditional access control solutions are inherently inadequate for collaborative systems because they are effective only in situations where the system knows in advance which users are going to access the resources and what are their access rights so that they can be predefined by the developers or security administrators, but in collaborative systems the number of users as well as their usage on resources is not static. Targeting collaborative systems, a fine grained, flexible, persistent trust-based model for protecting the access and usage of digital resources is defined in this paper using radial basis function neural network (RBFNN). RBFNN classifies the users requesting the resources as trustworthy and non-trustworthy based on their attributes. RBFNN is used for classification because of its ability to generalise well for even unseen data and non-iterative method employed in its training. A proof of concept implementation backed by extensive set of tests on the real data collected for one such collaborative systems, i.e. Enabling Grids for E-Science grid demonstrated that the design is sound for collaborative systems where access of resources are provided to large and unknown users with their variant set of requirements.     

Argumentation-enabled interest-based personalised recommender system

Recommender systems (RSs) use information filtering to recommend information of interest (to a user). Similarly, personalisation can be adopted for recommendations in e-market. We propose a new and innovative system called as interest-based recommender system (IBRS) for personalisation of recommendations. The IBRS is an agent-based RS that takes into account user's preferences. It can transform a standard product (or service) into a dedicated solution for an individual. The system discovers interesting product alternatives based on user's underlying mental attitudes (likes and dislikes) during the repair process using argumentation. The proposed method combines a hybrid RS approach with automated argumentation-based reasoning between agents. The system improves results by improving the recommendation repair activity. We consider a book recommendation application, for experiment to carry out the system's (objective and subjective) evaluation using standard metrics. The experiments confirm that the proposed IBRS improves user's acceptance of the product as compared with a traditional hybrid method and an argumentation-enabled state-of-the-art recommendation method. The system has been found to be more effective than its traditional counterpart when dealing with the new user problems.