Strength development of fly ash based composite material

The term „fly ash‟ is often used to describe any fine particulate material precipitated from the stack gases of industrial furnaces burning solid fuels. The amount of fly ash collected from furnaces on a single site can vary from less than one ton per day to several tons per minute. The characteristics and properties of different fly ashes depend on the nature of the fuel and the size of furnace used. Pulverization of solid fuels for the large furnaces used in power stations creates an immediate, urgent problem; dry fly ash has to be collected from the stack gases and disposed of quickly and safely. Fly ashes generally fall into one of two categories, depending on their origin and their chemical and mineralogical composition. Combustion of anthracite or bituminous coal generally produces low-calcium fly ashes; high-calcium fly ashes result from burning lignite or sub-bituminous coal. Both types contain a preponderance of amorphous glass. Composite material made of fly ash is used in many ways and is subject to a variety of different loading conditions, and so different types of stress develop. The compressive strength of concrete, one of its most important and useful properties and one of the most easily determined, is indicated by the unit stress required to cause failure of a specimen. In addition to being a significant indicator of load-carrying ability, strength is also indicative of other elements of quality concrete in a direct or indirect manner. In general, strong concrete will be more impermeable, better able to withstand severe exposure, and more resistant to wear. On the other hand, strong concrete may have greater shrinkage and susceptibility to cracking than a weaker material. Finally, the concrete-making properties of the various ingredients of the mix are usually measured in terms of the compressive strength

Fragment based tracking for scale and orientation adaptation

In this work, we propose a simple yet highly effective algorithm for tracking a target through significant scale and orientation change. We divide the target into a number of fragments and tracking of the whole target is achieved by coordinated tracking of the individual fragments. We use the mean shift algorithm to move the individual fragments to the nearest minima, though any other method like integral histograms could also be used. In contrast to the other fragment based approaches, which fix the relative positions of fragments within the target, we permit the fragments to move freely within certain bounds. Furthermore, we use a constant velocity Kalman filter for two purposes. Firstly, Kalman filter achieves robust tracking because of usage of a motion model. Secondly, to maintain coherence amongst the fragments, we use a coupled state transition model for the Kalman filter. Using the proposed tracking algorithm, we have experimented on several videos consisting of several hundred frames length each and obtained excellent results

On Stabilisation of Parametric Active Contours

Parametric active contours have been used extensively in computer vision for different tasks like segmentation and tracking. However, all parametric contours are known to suffer from the problem of frequent bunching and spacing out of curve points locally during the curve evolution. In a spline based implementation of active contours, this leads to occasional formation of loops locally, and subsequently the curve blows up due to instabilities. It has been shown earlier that in addition to usual evolution along the normal direction, the curve should also be evolved in the tangential direction for stability purposes. In this paper, we provide a mathematical basis for selecting such a suitable tangential component for stabilisation. We prove the boundedness of the evolved curve in this paper, and provide the physical significance. We demonstrate the usefulness of the proposed method with a number of experiments

Studies in molecular structure, symmetry and conformation I

Crystals of 1-aminocyclooctanecarboxylic acid hydrobromide are orthorhombic, with a = 26·026, b =7·087, c = 6·149, Z = 4 and space group P 2 1 2 1 2 1 .The structure was solved in projections by direct methods and later refined with three-dimensional data using a full-matrix least-squares treatment. All hydrogen atoms were located from a difference Fourier and the final R factor for the 1128 observed reflections was 8·62 %. The molecules are held together by a series of hydrogen bonds in a three-dimensional network. A detailed discussion of the intramolecular and the intermolecular features of the structure is presented. The cyclooctane ring is found to exist in the boat-chair conformation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44829/1/10870_2005_Article_BF01198532.pd

Distraction free evolution of active contours

We propose a novel energy term to make the curve evolution quite robust to spurious edges. The physical intuition behind the formulation is that an object edge is generally continuous, but it could be composed of weak and strong segments. We then formulate the energy term which depends on a second order measure defined on the contour Minimisation of this energy term yields a space varying curvature based curve evolution equation. An added advantage of the formulation is that this term also acts as the regularising term for smoothing the curve evolution. The proposed term can therefore be used in conjunction with any of the numerous gradient based active contour models. For our experimentation purpose, we have used the well-known gradient vector force model as the external force. We have performed a number of experiments on images and obtained good results

Stabilization of Parametric Active Contours Using a Tangential Redistribution Term

Depending on implementation, active contours have been classified as geometric or parametric active contours. Parametric contours, irrespective of representation, are known to suffer from the problem of irregular bunching and spacing out of curve points during the curve evolution. In a spline-based implementation of active contours, this leads to occasional formation of loops locally, and subsequently the curve blows up due to instabilities. In this paper, we analyze the reason for this problem and propose a solution to alleviate the same. We propose an ordinary differential equation (ODE) for controlling the curve parametrization during evolution by including a tangential force. We show that the solution of the proposed ODE is bounded. We demonstrate the effectiveness of the proposed method for segmentation and tracking tasks on closed as well as open contours

Adaptive smoothness based robust active contours

Active contours are a popular class of variational models used in computer vision for tracking and segmentation. The variational model consists of a data-fitting and a regularisation term. Depending on the data-fitting term, active contour models are classified as either gradient or region based models. An often overlooked but crucial aspect of these models is that these two terms are weighted by a manually set constant weight. This constant weight often leads to incorrect segmentation, particularly for gradient based energies. This failure rate is high in the presence of strong gradients nearby the target or when the object gradient is not uniformly strong. In such circumstances, setting the weight becomes a critical and often unsatisfying task. In this work, we propose a new spatially varying and dynamic curve evolution term for robust segmentation of gradient based models. In contrast to the majority of the existing work in literature which focuses on defining new data-fitting terms, the evolution term proposed here is related to the regularisation of evolution. The intuition here is that in images although object boundaries are generally continuous, the magnitude of the gradient map so generated is not uniformly strong. Therefore, any energy formulation which fixes the weights of the data-fitting and regularisation term will run into the problems mentioned above. In this work, we propose an energy term which defines the regularisation term in a spatially varying manner. The advantage of this term is that it is independent of the image based data-fitting energy term and hence can be plugged into the vast variety of the existing gradient based active contour models. (C) 2010 Elsevier B.V. All rights reserved