Catálogo de publicaciones - libros

This paper will discuss the proposed XML- based authoring environment. An authoring environment is proposed to accommodate authors in creating structured content without familiarity of XML techniques

This paper presents architecture for development of Hyperbook, using XML to describe the application domain to adapt the content of Hyperbook to the user’s behaviour. XML data-centric orientation makes it possible to describe application domain, data access and dynamic data composition functions. The system architecture of the Hyperbook is summarised. The characteristic of XML useful to manipulate data in a dynamic way is described. A general approach to data representation is described and the metadata and data presentation is presented.

This paper presents a novel image retrieval system (SVMBIR) based on dual tree complex wavelet transform (CWT) and support vector machines (SVM). We have shown that how one can improve the performance of image retrieval systems by assuming two attributes. Firstly, images that user needs through query image are similar to a group of images with same conception. Secondly, there exists non-linear relationship between feature vectors of different images and can be exploited very efficiently with the use of support vector machines. At first level, for low level feature extraction we have used dual tree complex wavelet transform because recently it is proven to be one of the best for both texture and color based features. At second level to extract semantic concepts, we grouped images of typical classes with the use of one against all support vector machines. We have also shown how one can use a correlation based distance metric for comparison of SVM distance vectors. The experimental results on standard texture and color datasets show that the proposed approach has superior retrieval performance over the existing linear feature combining techniques.

A region based visual and thermal image fusion technique based on k-means clustering algorithm is presented in this paper. This novel region fusion method segments regions of interest from thermal image using k-means clustering algorithm. Later on, these regions of interests are fused with visible image in DWFT domain. A prominent feature of our proposed technique is its near-real-time computation. Objective comparison of the scheme proposed in this paper has been done with other well known techniques. Experimental results and conclusion outlined in this paper will explain how well the proposed algorithm performs.

This report deals with the application of multi-valued logic in cellular automata. A four valued logic system with dibit representation has been considered in this case. The general properties and their relations to build such logical systems are also investigated and the question of implementation of this logical system in cellular automata environment has also been studied. It is shown, that chaotic fractals i.e, fractals as function of initial conditions are formed in such cases. It is interesting to note also that fractals so formed are multifractals and thus may have applications in analyzing natural fractal formation. Subject. terms: Multivalued Logic, Cellular Automata, Fractals.

The main focus of this paper is to define the operational semantics for the message passing strategy called Asynchronous Message Passing System (AMPS) used in the distributed programming language, LIPS (Language for Implementing Parallel/distributed Systems). AMPS is a point-to-point message passing system that does not use any message buffers. It is based on simple architecture and interfaces. In order to adequately provide implementation information for the message passing strategy, we have defined the operational semantics and the codes needed for the abstract machine of LIPS.

A computer code has been developed that simulates the performance of organic spin sandwiches. Chemical vapor deposition of polymer is simulated by placing monomers in random positions and allowing them to follow a random walk until joining some given linear polymer chain. Spontaneous magnetization in the intermediate region of the sandwich is simulated via Ising model. A genetic algorithm randomly flips a spin whenever the Hamiltonian of the system is optimized in energy space. Magnetization plateau turns out to be maximal when the border spins are parallel and is minimal when border spins are antiparallel. Simulation results are in agreement with recent experimental results for pyrochlore oxide superconductor

The paper presents a new framework for the extraction of region based affine invariant features with the view of object recognition in cluttered environments using the radon transform. The presented technique first normalizes an input image by performing data pre-whitening which reduces the problem by removing shearing deformations. Then four invariants are constructed by exploiting the properties of radon transform in combination with wavelets which enable the analysis of objects at multiple resolutions. The proposed technique makes use of an adaptive thresholding technique for the construction of invariants. Experimental results conducted using three different standard datasets confirm the validity of the proposed approach. Beside this the error rates obtained in terms of invariant stability in noisy conditions are significantly lower when compared to the method of moment invariants and the proposed invariants exhibit good feature disparity.

A discrete- time signal or time series is set of observations taken sequentially in time, space, or some other independent variable. Examples occur in various areas including engineering, natural sciences, economics, social sciences and medicine. Financial time series in particular are very difficult to model and predict, because of their inherent nature. Hence, it becomes essential to study the properties of signal and to develop quantitative techniques. The key characteristics of a time series are that the observations are ordered in time and that adjacent observations are related or dependent. In this paper a case study has been performed on the BSE and NSE index data and methods to classify the signals as Deterministic, Random or Stochastic and White Noise are explored. This pre-analysis of the signal forms the basis for further modeling and prediction of the time series.

Software Cost estimation at activity level is very much accurate than macro estimation with respect to phases of software development life cycle, but the same is very difficult to achieve[1]. Activity based estimation focus on key activities should not be left out and if any effort variance occurs it will be possible to track at particular activity level rather than affecting the entire activities[1]. Activity-based Software estimation based on work break down structure has been explained by collecting and analyzing the data for 12 Enhancements from Application service Maintenance project which were already delivered. This paper explains how to arrive accurate estimation at different micro level activities of Software Development Life Cycle(SDLC).