Abstract

The basic goal of pervasive computing is to develop technologies that allow smart devices to automatically adapt to changing environments and contexts, making the environment largely imperceptible to the user. One big barrier to the wide spread development of pervasive computing applications lies in the increased complexity of the programming task. There is a big gap between high-level application requirements, and low-level complex system organization and operations. Middleware can help bridge the gap — supporting rapid development and deployment of applications by domain experts with minimal programming expertise. However, pervasive computing poses new challenges to middleware research. Publish/Subscribe (pub/sub) middleware has many advantages when implementing systems for spontaneous, ad-hoc, pervasive applications. This paper describes REBECA architecture and the REBECA notification service. To efficiently support mobility, it is necessary to adequately deal with the uncertainty introduced by client movement. This paper sketches how this is done in the existing pub/sub middleware with REBECA and shows how to increase the efficiency of logical mobility by adapting the implementation of physical mobility.

Abstract

Accurate knowledge of a gradient magnetic field waveform is important for the measurement of diffusion coefficients . Diffusion coefficients are determined from the decay between an MR signal affected and an MR signal not affected by gradient pulses. Therefore the waveform of the gradients is essential from the point of view of accuracy. Short ramp times, amplitude of generated gradients and symmetry of positive and negative levels (i.e. an integral of two pulses with the same amplitude and inverse polarity is zero) are desirable.

Abstract

The fundamental mechanics relations governing the geometry of nanoclusters are reviewed and illustrations are presented. The Nanofabrication processes namely, ‘top-down i.e., it all begins from a bulk piece of material, which is then gradually or step-by-step removed to form objects in the nanometer-size regime and ‘bottom-up’ i.e., it all begins from atoms and molecules that get rearranged and assembled to larger nanostructures. It is the new paradigm for synthesis in the nanotechnology world as the ‘bottom-up’ approach allows a creation of different types of nano clusters. The Forces and Interactions of Self-Assembly and their relevant bonds affecting the bottom up fabrication have been discussed. Finally classical nucleation theory for clusters formation has been reported.

Abstract

Image based steganography uses the image as the cover media to overlay the payload. Spatial domain and frequency domain are the two familiar steganography techniques to carry embedding process on the cover image. Least Significant Bit (LSB) is commonly used spatial domain technique which is classified in to LSB replacement, LSB matching and matrix embedding. Further the embedding process may be sequential or random. This paper model an algorithm which give less distortion to the cover image during embedding process. Minimizing embedding impact and maximizing embedding capacity were few key factors of any steganography algorithm.  Higher the Peak Signal to Noise Ratio (PSNR) is lower the distortion. This is the fundamental principle followed in discriminating the distorted image (stego image) and cover image. Here matrix embedding technique is chosen to embed the secret image which is Huffman encoded. The Huffman encoded secret image is overlaid on the least significant bit of cover image through matrix embedding. As a result, the stego image is constructed with very less distortion when compared to the cover image. The stego image ends up with higher PSNR value. A secret image which cannot be embedded in a normal LSB embedding technique can be overlaid in this proposed technique since the secret image is Huffman encoded. PSNR value for different cover images and stego image with higher PSNR value is shown in this paper.

Abstract

Tube coils afford one of the cheapest means of obtaining heat transfer surface. Helical coils are frequently installed in vertical cylindrical vessel with or without an agitator, although free space is provided between the coil and vessel wall for circulation. Heating of viscous liquids and suspensions of particulate matter are important considerations in several industrial equipment including reactors. Several studies with mixing of suspension and with circulating coolant in a coil are available in literature. In present study, the overall heat transfer coefficients with natural convection between the coil surface and the liquid bath were investigated. The behaviour of overall heat transfer coefficient and coolant side heat transfer coefficients were observed for water (Newtonian), 3% soap and 1.5% starch solution (non-Newtonian) as hot bath liquids in the cylindrical vessel of a known dimension. Water as a coolant was supplied through helical coil immersed in the hot bath for batch cooling.

Abstract

This article aims at analyzing search engine use pattern of the engineering colleges resource centre in Tamilnadu.  Before pursuing an empirical analysis with reference to the application of information technology in the resource centres of engineering colleges, there is a need to spell out the content and meaning of information technology.  In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://Google.stanford.edu/ to engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them.

Abstract

In  the  recent  years,  Bayesian  Net  (BN)  is  an  increasingly  popular  formalism  for reasoning and  decision-making  in  problems  that   involve  uncertainty  and probabilistic reasoning. Bayesian Net gives the new advancements and innovations in Threatened  Tree Species   and   also   fulfilling   the   barriers   between   Knowledge Representation   and Artificial   intelligence.  The  species   degradation   calls   for  uncertainty  management  technique  that  aims  at  developing  knowledge  base  and  evaluating  the  status  of  the  species.  BN is a machine learning tool to provide an opportunity for predicting the species uncertainties in an Artificial intelligence system.

This paper reports a comparison of BN-based and subjective (elicit-based) prediction modeling and hence, relevant inference examples have been taken from the generated conditional  probability  table  (CPT)  so  as  to  define  decision  making  of  the  problem domain. The results demonstrate the performance prediction and inference BN model for   biological   variables   or   knowledge   base   via   Three-Phase-Dependency Analysis algorithm.