Replicode: A Constructivist Programming Paradigm and Language

Replicode is a language designed to encode short parallel programs and executable models, and is centered on the notions of extensive pattern-matching and dynamic code production. The language is domain independent and has been designed to build systems that are modelbased and model-driven, as production systems that can modify their own code. More over, Replicode supports the distribution of knowledge and computation across clusters of computing nodes. This document describes Replicode and its executive, i.e. the system that executes Replicode constructions. The Replicode executive is meant to run on Linux 64 bits and Windows 7 32/64 bits platforms and interoperate with custom C++ code. The motivations for the Replicode language, the constructivist paradigm it rests on, and the higher-level AI goals targeted by its construction, are described by Thórisson (2012), Nivel and Thórisson (2009), and Thórisson and Nivel (2009a, 2009b). An overview presents the main concepts of the language. Section 3 describes the general structure of Replicode objects and describes pattern matching. Section 4 describes the execution model of Replicode and section 5 describes how computation and knowledge are structured and controlled. Section 6 describes the high-level reasoning facilities offered by the system. Finally, section 7 describes how the computation is distributed over a cluster of computing nodes. Consult Annex 1 for a formal definition of Replicode, Annex 2 for a specification of the executive, Annex 3 for the specification of the executable code format (r-code) and its C++ API, and Annex 4 for the definition of the Replicode Extension C++ API

Performance of the ATLAS Trigger System in 2010

Proton–proton collisions at √s=7 TeV and heavy ion collisions at √sNN=276 TeV were produced by the LHC and recorded using the ATLAS experiment’s trigger system in 2010. The LHC is designed with a maximum bunch crossing rate of 40 MHz and the ATLAS trigger system is designed to record approximately 200 of these per second. The trigger system selects events by rapidly identifying signatures of muon, electron, photon, tau lepton, jet, and B meson candidates, as well as using global event signatures, such as missing transverse energy. An overview of the ATLAS trigger system, the evolution of the system during 2010 and the performance of the trigger system components and selections based on the 2010 collision data are shown. A brief outline of plans for the trigger system in 2011 is presented

Performance and Comparative Analysis of the Two Contrary Approaches for Detecting Near Duplicate Web Documents in Web Crawling

Recent years have witnessed the drastic development of World Wide Web (WWW). Information is being accessible at the finger tip anytime anywhere through the massive web repository. The performance and reliability of web engines thus face huge problems due to the presence of enormous amount of web data. The voluminous amount of web documents has resulted in problems for search engines leading to the fact that the search results are of less relevance to the user. In addition to this, the presence of duplicate and near-duplicate web documents has created an additional overhead for the search engines critically affecting their performance. The demand for integrating data from heterogeneous sources leads to the problem of near-duplicate web pages. The detection of near duplicate documents within a collection has recently become an area of great interest. In this research, we have presented an efficient approach for the detection of near duplicate web pages in web crawling which uses keywords and the distance measure. Besides that, G.S. Manku et al.’s fingerprint based approach proposed in 2007 was considered as one of the “state-of-the-art" algorithms for finding near-duplicate web pages. Then we have implemented both the approaches and conducted an extensive comparative study between our similarity score based approach and G.S. Manku et al.’s fingerprint based approach. We have analyzed our results in terms of time complexity, space complexity, Memory usage and the confusion matrix parameters. After taking into account the above mentioned performance factors for the two approaches, the comparison study clearly portrays our approach the better (less complex) of the two based on the factors considered.DOI:http://dx.doi.org/10.11591/ijece.v2i6.1746