paper discuss the impact of different process frameworks along the various key parameters that synthesizes views from areas such as information systems development, enterprise modeling and work flow management. The idea behind this comparison study of Next Generation Network (NGN) Business Process Framework is to help practitioners to identify different views one should consider whenever applying a Business Process Framework implementation project. KeywordseTOM
domain specific crawler, as diverse from a general web search engine, focuses on a specific segment of web content. They are also called vertical or topical search engines. Common vertical search engines are meant for shopping, automotive industry, legal information, medical information, scholarly literature, and travel. Examples of vertical search engines are Trulia.com, Mocavo.com and Yelp. In contrast to genera lpurpose Web search engines, which attempt to index large portions of the World Wide Web using a web crawler, vertical search engines typically use a domain specific crawler that attempts to index only Web pages that are relevant to a pre-defined topic or set of topics. Vertical search offers several potential benefits over general search such as greater precision due to their limited scope, leverage domain knowledge including taxonomies and ontology and support of specific unique user tasks. This paper aims at analyzing the machine learning Techniques namely ANN, SVM and Hi-SVM being used for Web Page Classification and suggesting suitable improvements. Here a crawling framework has been designed and developed that allows flexible addition of new classifiers. This crawler has been used for classification of web content for few domains. The crawlers themselves are implemented as multithreaded objects that run concurrently. The results show that Hi-SVM is a better choice for guiding a topical crawler when compared to Support Vector Machine and Neural Network. The comparative analysis of the three classifier techniques namely ANN, SVM and Hi-SVM showed that the performance of Hi-SVM is most efficient. KeywordsSVM, HiSVM, VSM, ROC, REC, POS, WSD, SOE.
‘Sixth sense’ is a way of opening up to the vast world which cannot be identified by five senses. Mr. Steve Mann in 1990 started working on this idea which led to the innovation of ‘Sixth sense technology’ using a Telepointer, a wearable device for the experience of visuals on real world objects. His wok was then carried on by a younger lad, Pranav Mistry. Sixth sense device is based on gesture interactions and its interface, a kind of device which doesn’t need to carry any big attribute like a camera or watch. Six sense technology is a new & interesting stream of technology, which can be the most approachable as it is all about interacting with the digiworld directly. The device uses mirror, camera, pocket projector, smart phone & color markers to identify any object or some view and then it imparts it over the real world.
In this paper, we discuss about basic operating systems, get an overview of the internal processes associated with an operating system and understand its connection with the kernel and the hardware. We then move on to Virtualization by introducing Vagrant, an operating system virtualization software that allows you to run virtual machines on your system and configure them the way you want to suit your needs, and discuss about virtualization on cloud.
In this paper, we are implementing the Convolutional encoder and viterbi decoder with code rate 2/3 using verilog. The main issue of this paper is to implement the RTL level model of Convolutional encoder and viterbi decoder, with the testing results of behavior model. We tried to achieve a low silicon cost. The viterbi algorithm, used for Convolutional codes extensively employed decoding algorithm for Convolutional codes. This paper is realized using verilog HDL. It is simulated and synthesized using Modelsim Altera 10.1d. General Terms Convolutional codes were first introduced by Elias in 1955 as an alternative to block codes. Convolutional codes differ from block codes in that the encoder contains memory and the n encoder outputs at any time unit depend not only on the k inputs but also on m previous input block. In 1963, Massey proposed a less efficient but simpler to implement decoding method called threshold decoding. Then in 1967, Viterbi proposed a maximum likelihood decoding scheme that was easy to implement for codes. This scheme is called viterbi decoding.