Bandwagon, underdog, and political competition: The uni-dimensional case by

Abstract: This research proposes a new strategy where documents are encoded into string vectors and modified version of KNN to be adaptable to string vectors for text categorization. Traditionally, when KNN are used for pattern classification, raw data should be encoded into numerical vectors

. Our objective is to determine the efficiency of a user-level DSM implementation on commercially available workstations and operating systems. We achieved good speedups on the 8-processor ATM network for Jacobi (7.4), TSP (7.2), Quicksort (6.3), and ILINK (5.7). For a slightly modified version

The iterative algorithm recently proposed by Waxman for solving eigenvalue problems, which relies on the method of moments, has been modified to improve its convergence considerably without sacrificing its benefits or elegance. The suggested modification is based on methods to calculate low

Stream ciphers in general tend to be weak since they lack the benefit of diffusion. It is for this reason alone that the Vigenère cipher is able to be cracked. Without the ability to detect cycles, and intern, derive the key length, the Vigenère cipher would be highly secure. By adding a few bits of random padding to each byte, one can diffuse the statistical retentiveness found within most messages. The exact quantity of pad will be determined by a one way function in an effort to eliminate the distinguishably of the message bits from the padded random bits. This methodology moderately increases the size of the cipher text, but greatly increases the security of the cipher Key words: Cryptography, Vigenere, Cypher.

We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboost can be used to fit interpretable models of different complexity. As an example we use mboost to predict the body fat based on anthropometric measurements throughout the tutorial. 1

In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LS-SVMs), a least squares cost function is proposed so as to obtain a linear set

of arbitrary circuits, it suffices to construct an encryption scheme that can evaluate (slightly augmented versions of) its own decryption circuit; we call a scheme that can evaluate its (augmented) decryption circuit bootstrappable. Next, we describe a public key encryption scheme using ideal lattices

This article describes the semantics of the language of statecharts as implenented in the STATEMATE system [Harel et al. 1990; Harel and Politi 1996]. The initial version of this semantics was developed by a team about.10 years ago. With the added experience of the users of the system it has since

by local extrema of normalized derivatives over scale. 3) An affine-adapted Harris detector determines the location of interest points. A multi-scale version of this detector is used for initialization. An iterative algorithm then modifies location, scale and neighbourhood of each point and converges