An ontology enhanced parallel SVM for scalable spam filter training

This is the post-print version of the final paper published in Neurocomputing. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Spam, under a variety of shapes and forms, continues to inflict increased damage. Varying approaches including Support Vector Machine (SVM) techniques have been proposed for spam filter training and classification. However, SVM training is a computationally intensive process. This paper presents a MapReduce based parallel SVM algorithm for scalable spam filter training. By distributing, processing and optimizing the subsets of the training data across multiple participating computer nodes, the parallel SVM reduces the training time significantly. Ontology semantics are employed to minimize the impact of accuracy degradation when distributing the training data among a number of SVM classifiers. Experimental results show that ontology based augmentation improves the accuracy level of the parallel SVM beyond the original sequential counterpart

LFI 30 and 44 GHz receivers Back-End Modules

The 30 and 44 GHz Back End Modules (BEM) for the Planck Low Frequency Instrument are broadband receivers (20% relative bandwidth) working at room temperature. The signals coming from the Front End Module are amplified, band pass filtered and finally converted to DC by a detector diode. Each receiver has two identical branches following the differential scheme of the Planck radiometers. The BEM design is based on MMIC Low Noise Amplifiers using GaAs P-HEMT devices, microstrip filters and Schottky diode detectors. Their manufacturing development has included elegant breadboard prototypes and finally qualification and flight model units. Electrical, mechanical and environmental tests were carried out for the characterization and verification of the manufactured BEMs. A description of the 30 and 44 GHz Back End Modules of Planck-LFI radiometers is given, with details of the tests done to determine their electrical and environmental performances. The electrical performances of the 30 and 44 GHz Back End Modules: frequency response, effective bandwidth, equivalent noise temperature, 1/f noise and linearity are presented

Feasibility report: Delivering case-study based learning using artificial intelligence and gaming technologies

This document describes an investigation into the technical feasibility of a game to support learning based on case studies. Information systems students using the game will conduct fact-finding interviews with virtual characters. We survey relevant technologies in computational linguistics and games. We assess the applicability of the various approaches and propose an architecture for the game based on existing techniques. We propose a phased development plan for the development of the game