Writer Identification Using Inexpensive Signal Processing Techniques

We propose to use novel and classical audio and text signal-processing and otherwise techniques for "inexpensive" fast writer identification tasks of scanned hand-written documents "visually". The "inexpensive" refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate "visual" identification by "looking" at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.Comment: 9 pages; 1 figure; presented at CISSE'09 at http://conference.cisse2009.org/proceedings.aspx ; includes the the application source code; based on MARF described in arXiv:0905.123

Machine-Related Backgrounds in the SiD Detector at ILC

With a multi-stage collimation system and magnetic iron spoilers in the tunnel, the background particle fluxes on the ILC detector can be substantially reduced. At the same time, beam-halo interactions with collimators and protective masks in the beam delivery system create fluxes of muons and other secondary particles which can still exceed the tolerable levels for some of the ILC sub-detectors. Results of modeling of such backgrounds in comparison to those from the e+ e- interactions are presented in this paper for the SiD detector.Comment: 29 pages, 34 figures, 7 table