A Robust Image Hashing Algorithm Resistant Against Geometrical Attacks

This paper proposes a robust image hashing method which is robust against common image processing attacks and geometric distortion attacks. In order to resist against geometric attacks, the log-polar mapping (LPM) and contourlet transform are employed to obtain the low frequency sub-band image. Then the sub-band image is divided into some non-overlapping blocks, and low and middle frequency coefficients are selected from each block after discrete cosine transform. The singular value decomposition (SVD) is applied in each block to obtain the first digit of the maximum singular value. Finally, the features are scrambled and quantized as the safe hash bits. Experimental results show that the algorithm is not only resistant against common image processing attacks and geometric distortion attacks, but also discriminative to content changes

Wideband wattmeter for instant measurement of real power

Portable, solid state wattmeter with wideband (dc to 1 MHz) linear multiplier which provides true four quadrant operation permitting instantaneous indication of real power as oscilloscope display is described

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series

Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics

Union and Union Threat Premiums Among Graduate Student Stipends

To inform the ongoing debate over graduate student unionization, the author tests for the presence of union-related premiums among teaching and research assistant stipends using data from The Chronicle of Higher Education’s survey of departments in six fields in 2000, 2001, and 2003. Ordinary least squares and instrumental variables methods reveal union and union threat premiums among teaching assistant stipends. There is little evidence of union-related premiums among research assistant stipends. Specifications controlling for union composition or using employment weights reveal that the teaching assistant only union premium is positive for teaching assistant stipends and negative for research assistant stipends. This suggests that collectively bargained contracts may yield benefits for teaching assistants at the expense of research assistants when the latter are excluded from the bargaining unit. There is a positive premium to joint teaching and research assistant unions for teaching assistant stipends and no effect for research assistant stipends